diff --git a/include/rosa/agent/History.hpp b/include/rosa/agent/History.hpp
index a10bb1e..8cca4a5 100644
--- a/include/rosa/agent/History.hpp
+++ b/include/rosa/agent/History.hpp
@@ -1,613 +1,615 @@
 //===-- rosa/agent/History.hpp ----------------------------------*- C++ -*-===//
 //
 //                                 The RoSA Framework
 //
 // Distributed under the terms and conditions of the Boost Software License 1.0.
 // See accompanying file LICENSE.
 //
 // If you did not receive a copy of the license file, see
 // http://www.boost.org/LICENSE_1_0.txt.
 //
 //===----------------------------------------------------------------------===//
 ///
 /// \file rosa/agent/History.hpp
 ///
 /// \author David Juhasz (david.juhasz@tuwien.ac.at)
 ///
 /// \date 2017
 ///
 /// \brief Definition of *history* *functionality*.
 ///
 //===----------------------------------------------------------------------===//
 
 #ifndef ROSA_AGENT_HISTORY_HPP
 #define ROSA_AGENT_HISTORY_HPP
 
 #include "rosa/agent/Functionality.h"
 
 #include "rosa/config/config.h"
 
 #include "rosa/support/debug.hpp"
 #include "rosa/support/type_helper.hpp"
 
 #include <algorithm>
 #include <array>
 #include <limits>
 #include <vector>
 
 #include <math.h>
 
 namespace rosa {
 namespace agent {
 
 // @benedikt: todo: assert in history, which checks if push_back worked
 
 /// Retention policies defining what a \c rosa::agent::History instance should
 /// do when the number of recorded entries reached its capacity.
 enum class HistoryPolicy {
   SRWF, ///< Stop Recording When Full -- no new entry is recorded when full
   FIFO, ///< First In First Out -- overwrite the earliest entry with a new one
   LIFO  ///< Last In First Out -- overwrite the latest entry with a new one
 };
 
 template <typename T, HistoryPolicy P> class History : public Functionality {
 
 public:
   History(void) noexcept = default;
 
   /// Destroys \p this object.
   virtual ~History(void) = default;
 
   /// Tells the retention policy applied to \p this object.
   ///
   /// \return \c rosa::agent::History::P
   static constexpr HistoryPolicy policy(void) noexcept { return P; }
 
   /// Tells how many entries may be recorded by \c this object.
   ///
   /// \note The number of entries that are actually recorded may be smaller.
   ///
   /// \return The max number of entries that may be recorded
   virtual size_t maxLength(void) const noexcept = 0;
 
   /// Tells how many entries are currently recorded by \p this object.
   ///
   /// \return number of entries currently recorded by \p this object.
   ///
   /// \post The returned value cannot be larger than the capacity of \p this
   /// object:\code
   /// 0 <= numberOfEntries() && numberOfEntries <= lengthOfHistory()
   /// \endcode
   virtual size_t numberOfEntries(void) const noexcept = 0;
 
   /// Tells if \p this object has not recorded anything yet.
   ///
   /// \return if \p this object has no entries recorded
   bool empty(void) const noexcept { return numberOfEntries() == 0; }
 
   /// Tells if the history reached it's maximum length
   ///
   /// \return if the history reached it's maximum length.
   bool full(void) const noexcept { return numberOfEntries() == maxLength(); }
 
   /// Gives a constant lvalue reference to an entry stored in \p this object.
   ///
   /// \note The recorded entries are indexed starting from the latest one.
   ///
   /// \param I the index at which the stored entry to take from
   ///
   /// \pre \p I is a valid index:\code
   /// 0 <= I && I < numberOfEntries()
   /// \endcode
   virtual const T &entry(const size_t I = 0) const noexcept = 0;
 
   /// Removes all entries recorded in \p this object.
   virtual void clear() noexcept = 0;
 
 private:
   /// Pushes a new entry into the history.
   ///
   /// \note The earliest entry gets overwritten if the history is full.
   ///
   /// \param V value to push into the history
   virtual void pushBack(const T &V) noexcept = 0;
 
   /// Replaces the most recent entry in the history.
   ///
   /// \param V value to replace the most current value with
   virtual void replaceFront(const T &V) noexcept = 0;
 
 public:
   /// Adds a new entry to \p this object and tells if the operation was
   /// successful.
   ///
   /// \note Success of the operation depends on the actual policy.
   ///
   /// \param V value to store
   ///
   /// \return if \p V was successfully stored
   bool addEntry(const T &V) noexcept {
     switch (P) {
     default:
       ROSA_CRITICAL("unkown HistoryPolicy");
     case HistoryPolicy::LIFO:
       if (full()) {
         replaceFront(V);
         return true;
       }
     case HistoryPolicy::SRWF:
       if (full()) {
         return false;
       }
     // \note Fall through to FIFO which unconditionally pushes the new entry.
     case HistoryPolicy::FIFO:
       // FIFO and SRWF not full.
       pushBack(V);
       return true;
     }
   }
 
   /// Tells the trend set by the entries recorded by \p this object.
   ///
   /// The number of steps to go back when calculating the trend is defined as
   /// argument to the function.
   ///
   /// \note The number of steps that can be made is limited by the number of
   /// entries recorded by \p this object.
   ///
   /// \note The function is made a template only to be able to use
   /// \c std::enable_if.
   ///
   /// \tparam X always use the default!
   ///
   /// \param D number of steps to go back in *history*
   ///
   /// \return trend set by analyzed entries
   ///
   /// \pre Statically, \p this object stores signed arithmetic values:\code
   /// std::is_arithmetic<T>::value && std::is_signed<T>::value
   /// \endcode Dynamically, \p D is a valid number of steps to take:\code
   /// 0 <= D && D < lengthOfHistory()
   /// \endcode
   template <typename X = T>
   typename std::enable_if<
       std::is_arithmetic<X>::value && std::is_signed<X>::value, X>::type
   trend(const size_t D) const noexcept {
     STATIC_ASSERT((std::is_same<X, T>::value), "not default template arg");
     ASSERT(0 <= D && D < maxLength()); // Boundary check.
     if (numberOfEntries() < 2 || D < 1) {
       // No entries for computing trend.
       return {}; // Zero element of \p T
     } else {
       // Here at least two entries.
       // \c S is the number of steps that can be done.
       const size_t S = std::min(numberOfEntries() - 1, D);
       size_t I = S;
 
       // Compute trend with linear regression.
       size_t SumIndices = 0;
       T SumEntries = {};
       T SumSquareEntries = {};
       T SumProduct = {};
       while (I > 0) {
         // \note Indexing for the regression starts in the past.
         const size_t Index = S - I;
         const T Entry = entry(--I);
         SumIndices += Index;
         SumEntries += Entry;
         SumSquareEntries += Entry * Entry;
         SumProduct += Entry * Index;
       }
 
       return (SumProduct * S - SumEntries * SumIndices) /
              (SumSquareEntries * S - SumEntries * SumEntries);
     }
   }
 
   /// Tells the average absolute difference between consecutive entries recorded
   /// by \p this object
   /// The number of steps to go back when calculating the average is defined as
   /// argument to the function.
   ///
   /// \note The number of steps that can be made is limited by the number of
   /// entries recorded by \p this object.
   ///
   /// \note The function is made a template only to be able to use
   /// \c std::enable_if.
   ///
   /// \tparam X always use the default!
   ///
   /// \param D number of steps to go back in *history*
   ///
   /// \pre Statically, \p this object stores arithmetic values:\code
   /// std::is_arithmetic<T>::value
   /// \endcode Dynamically, \p D is a valid number of steps to take:\code
   /// 0 <= D && D < lengthOfHistory()
   /// \endcode
   template <typename X = T>
   typename std::enable_if<std::is_arithmetic<X>::value, size_t>::type
   averageAbsDiff(const size_t D) const noexcept {
     STATIC_ASSERT((std::is_same<X, T>::value), "not default template arg");
     ASSERT(0 <= D && D < maxLength()); // Boundary check.
     if (numberOfEntries() < 2 || D < 1) {
       // No difference to average.
       return {}; // Zero element of \p T
     } else {
       // Here at least two entries.
       // \c S is the number of steps that can be done.
       const size_t S = std::min(numberOfEntries() - 1, D);
 
       // Sum up differences as non-negative values only, hence using an
       // unsigned variable for that.
       size_t Diffs = {}; // Init to zero.
       // Count down entry indices and sum up all the absolute differences.
       size_t I = S;
       T Last = entry(I);
       while (I > 0) {
         T Next = entry(--I);
         Diffs += Last < Next ? Next - Last : Last - Next;
         Last = Next;
       }
       // Return the average of the summed differences.
       return Diffs / S;
     }
   }
 
   /// Tells the average of all entries recorded by \p this object
   ///
   /// \tparam R type of the result
   template <typename R> R average() const noexcept {
     R Average = 0;
     for (size_t I = 0; I < numberOfEntries(); I++) {
       Average += entry(I);
     }
     Average /= numberOfEntries();
     return Average;
   }
 
   /// Tells the sigma of all entries recorded by \p this object
   ///
   /// \tparam R type of the result
   template <typename R> R sigma() const noexcept {
     R Average = average();
     R Sigma = 0;
     for (size_t I = 0; I < numberOfEntries(); I++) {
       Sigma += pow((entry(I)-Average),2);
     }
     Sigma = sqrt(1.0/numberOfEntries()*Sigma);
     return Sigma;
   }
-
-  // Experiment
-  // Note from Benedikt: I think this will not return the median because the
-  // history is not sorted
-  template <typename R> R median() const noexcept {
-    if (numberOfEntries() % 2 == 0) {
-      return (entry(numberOfEntries() / 2 - 1) + entry(numberOfEntries() / 2)) /
-             2;
-    } else {
-      return entry(numberOfEntries() / 2);
-    }
-  }
 };
 
 /// Implements *history* by recording and storing values.
 /// The length of the underlying std::array is static and must be set at
 /// compile-time
 ///
 /// \note Not thread-safe implementation, which should not be a problem as any
 /// instance of \c rosa::agent::Functionality is an internal component of a
 /// \c rosa::Agent, which is the basic unit of concurrency.
 ///
 /// \tparam T type of values to store
 /// \tparam N number of values to store at most
 /// \tparam P retention policy to follow when capacity is reached
 ///
 /// \invariant The size of the underlying \c std::array is `N + 1`:\code
 /// max_size() == N + 1 && N == max_size() - 1
 /// \endcode
 template <typename T, size_t N, HistoryPolicy P>
 class StaticLengthHistory : public History<T, P>, private std::array<T, N + 1> {
 
   // Bring into scope inherited functions that are used.
   using std::array<T, N + 1>::max_size;
   using std::array<T, N + 1>::operator[];
 
   /// The index of the first data element in the circular buffer.
   size_t Data;
 
   /// The index of the first empty slot in the circular buffer.
   size_t Space;
 
 public:
   using History<T, P>::policy;
   using History<T, P>::empty;
   using History<T, P>::full;
   using History<T, P>::addEntry;
   using History<T, P>::trend;
   using History<T, P>::averageAbsDiff;
 
   /// Creates an instances by initializing the indices for the circular buffer.
   StaticLengthHistory(void) noexcept : Data(0), Space(0) {}
 
   /// Destroys \p this object.
   ~StaticLengthHistory(void) override = default;
 
   /// Tells how many entries may be recorded by \c this object.
   ///
   /// \note The number of entries that are actually recorded may be smaller.
   ///
   /// \return \c rosa::agent::History::N
   size_t maxLength(void) const noexcept override { return N; }
 
   /// Tells how many entries are currently recorded by \p this object.
   ///
   /// \return number of entries currently recorded by \p this object.
   ///
   /// \post The returned value cannot be larger than the capacity of \p this
   /// object:\code
   /// 0 <= numberOfEntries() && numberOfEntries <= lengthOfHistory()
   /// \endcode
   size_t numberOfEntries(void) const noexcept override {
     return Data <= Space ? Space - Data : max_size() - Data + Space;
   }
 
   /// Gives a constant lvalue reference to an entry stored in \p this object.
   ///
   /// \note The recorded entries are indexed starting from the latest one.
   ///
   /// \param I the index at which the stored entry to take from
   ///
   /// \pre \p I is a valid index:\code
   /// 0 <= I && I < numberOfEntries()
   /// \endcode
   const T &entry(const size_t I = 0) const noexcept override {
     ASSERT(0 <= I && I < numberOfEntries()); // Boundary check.
     // Position counted back from the last recorded entry.
     typename std::make_signed<const size_t>::type Pos = Space - (1 + I);
     // Actual index wrapped around to the end of the buffer if negative.
     return (*this)[Pos >= 0 ? Pos : max_size() + Pos];
   }
 
   /// Removes all entries recorded in \p this object.
   void clear() noexcept override {
     Data = 0;
     Space = 0;
   }
 
 private:
   /// Pushes a new entry into the circular buffer.
   ///
   /// \note The earliest entry gets overwritten if the buffer is full.
   ///
   /// \param V value to push into the buffer
   void pushBack(const T &V) noexcept override {
     // Store value to the first empty slot and step Space index.
     (*this)[Space] = V;
     Space = (Space + 1) % max_size();
     if (Data == Space) {
       // Buffer was full, step Data index.
       Data = (Data + 1) % max_size();
     }
   }
 
   /// Replaces the most recent entry in the history.
   ///
   /// \param V value to replace the most current value with
   void replaceFront(const T &V) noexcept override {
     (*this)[(Space - 1) % max_size()] = V;
   }
 };
 
 /// Adds a new entry to a \c rosa::agent::History instance.
 ///
 /// \note The result of \c rosa::agent::History::addEntry is ignored.
 ///
 /// \tparam T type of values stored in \p H
 /// \tparam N number of values \p H is able to store
 /// \tparam P retention policy followed by \p H when capacity is reached
 ///
 /// \param H to add a new entry to
 /// \param V value to add to \p H
 ///
 /// \return \p H after adding \p V to it
 template <typename T, size_t N, HistoryPolicy P>
 StaticLengthHistory<T, N, P> &operator<<(StaticLengthHistory<T, N, P> &H,
                                          const T &V) noexcept {
   H.addEntry(V);
   return H;
 }
 
 /// Implements *DynamicLengthHistory* by recording and storing values.
 ///
 /// \note Not thread-safe implementation, which should not be a problem as any
 /// instance of \c rosa::agent::Functionality is an internal component of a
 /// \c rosa::Agent, which is the basic unit of concurrency.
 ///
 /// \tparam T type of values to store
 /// \tparam P retention policy to follow when capacity is reached
 template <typename T, HistoryPolicy P>
 class DynamicLengthHistory : public History<T, P>, private std::vector<T> {
 
 private:
   // Bring into scope inherited functions that are used.
   using std::vector<T>::size;
   using std::vector<T>::resize;
   using std::vector<T>::push_back;
   using std::vector<T>::pop_back;
   using std::vector<T>::max_size;
   /// The current length of the DynamicLengthHistory.
   size_t Length;
 
 public:
   // Bring into scope inherited functions that are used.
   using std::vector<T>::erase;
   using std::vector<T>::begin;
   using std::vector<T>::end;
   using std::vector<T>::rbegin;
   using std::vector<T>::rend;
   using std::vector<T>::operator[];
 
   // Bring into scope inherited functions that are used.
   using History<T, P>::policy;
   using History<T, P>::empty;
   using History<T, P>::full;
   using History<T, P>::addEntry;
   using History<T, P>::trend;
   using History<T, P>::averageAbsDiff;
 
   /// Creates an instances by setting an initial length
   DynamicLengthHistory(size_t Length) noexcept : Length(Length) {}
 
   /// Destroys \p this object.
   ~DynamicLengthHistory(void) override = default;
 
   /// Tells how many entries may be recorded by \c this object.
   ///
   /// \note The number of entries that are actually recorded may be smaller.
   ///
   /// \return \c rosa::agent::DynamicLengthHistory::N
   size_t maxLength(void) const noexcept override { return Length; }
 
   /// Tells how many entries are currently recorded by \p this object.
   ///
   /// \return number of entries currently recorded by \p this object.
   ///
   /// \post The returned value cannot be larger than the capacity of \p this
   /// object:\code
   /// 0 <= numberOfEntries() && numberOfEntries <=
   /// lengthOfHistory() \endcode
   size_t numberOfEntries(void) const noexcept override { return size(); }
 
   /// Gives a constant lvalue reference to an entry stored in \p this object.
   ///
   /// \note The recorded entries are indexed starting from the latest one.
   ///
   /// \param I the index at which the stored entry to take from
   ///
   /// \pre \p I is a valid index:\code
   /// 0 <= I && I < numberOfEntries()
   /// \endcode
   const T &entry(const size_t I = 0) const noexcept override {
     ASSERT(0 <= I && I < numberOfEntries()); // Boundary check.
     return this->operator[](size() - I - 1);
   }
 
   /// Removes all entries recorded in \p this object.
   void clear() noexcept override { erase(begin(), end()); }
 
   /// Sort all entries in ascending order.
   void sortAscending(void) noexcept { std::sort(begin(), end()); }
 
   /// Sort all entries in descending order.
   void sortDescending(void) noexcept { std::sort(rbegin(), rend()); }
 
   /// Delets one element of the history.
   ///
   /// \param V the element which shall be deleted.
   void deleteEntry(T &V) {
     auto it = std::find(begin(), end(), V);
 
     if (it != end()) {
       erase(it);
     }
   }
 
   /// Gives back the lowest entry of the history.
   ///
   /// \return the lowest entry. In case of an empty history, the maximum value
   /// of the chosen data type is returned.
   T lowestEntry() {
     auto it = std::min_element(begin(), end());
 
     if (it == end()) {
       return std::numeric_limits<T>::max();
     } else {
       return *it;
     }
   }
 
   /// Gives back the highest entry of the history.
   ///
   /// \return the highest entry. In case of an empty history, the minimum value
   /// of the chosen data type is returned.
   T highestEntry() {
     auto it = std::max_element(begin(), end());
 
     if (it == end()) {
       return std::numeric_limits<T>::min();
     } else {
       return *it;
     }
   }
 
 private:
   /// Pushes a new entry into the circular buffer.
   ///
   /// \note The earliest entry gets overwritten if the buffer is full.
   ///
   /// \param V value to push into the buffer
   void pushBack(const T &V) noexcept override {
     if (full()) {
       erase(begin());
     }
     push_back(V);
   }
 
   /// Replaces the most recent entry in the history.
   ///
   /// \param V value to replace the most current value with
   void replaceFront(const T &V) noexcept override {
     (void)pop_back();
     push_back(V);
   }
 
 public:
   /// Resizes the History length. If the new length is smaller than the number
   /// of currently stored values, values are deleted according to the
   /// HistoryPolicy.
   ///
   /// @param NewLength The new Length of the History.
   void setLength(size_t NewLength) noexcept {
     Length = NewLength;
     if (NewLength < numberOfEntries()) {
       switch (P) {
       default:
         ROSA_CRITICAL("unkown HistoryPolicy");
       case HistoryPolicy::LIFO:
       case HistoryPolicy::SRWF:
         // Delete last numberOfEntries() - NewLength items from the back
         erase(begin() + NewLength, end());
         break;
       case HistoryPolicy::FIFO:
         // Delete last numberOfEntries() - NewLength items from the front
         erase(begin(), begin() + (numberOfEntries() - NewLength));
         break;
       }
     }
     this->resize(Length);
   }
+
+  // Calculates the median of the history
+  // \return the median of the history
+  template <typename R> R median() noexcept {
+    sortAscending();
+    if (numberOfEntries() == 0) {
+      return 0;
+    } else if (numberOfEntries() % 2 == 0) {
+      return (entry(numberOfEntries() / 2 - 1) + entry(numberOfEntries() / 2)) /
+             2;
+    } else {
+      return entry(numberOfEntries() / 2);
+    }
+  }
 };
 
 /// Adds a new entry to a \c rosa::agent::DynamicLengthHistory instance.
 ///
 /// \note The result of \c rosa::agent::DynamicLengthHistory::addEntry is
 /// ignored.
 ///
 /// \tparam T type of values stored in \p H
 /// \tparam P retention policy followed by \p H when capacity is reached
 ///
 /// \param H to add a new entry to
 /// \param V value to add to \p H
 ///
 /// \return \p H after adding \p V to it
 template <typename T, HistoryPolicy P>
 DynamicLengthHistory<T, P> &operator<<(DynamicLengthHistory<T, P> &H,
                                        const T &V) noexcept {
   H.addEntry(V);
   return H;
 }
 } // End namespace agent
 } // End namespace rosa
 
 #endif // ROSA_AGENT_HISTORY_HPP
diff --git a/include/rosa/agent/SignalState.hpp b/include/rosa/agent/SignalState.hpp
index ccad719..2cfc654 100644
--- a/include/rosa/agent/SignalState.hpp
+++ b/include/rosa/agent/SignalState.hpp
@@ -1,684 +1,684 @@
 //===-- rosa/agent/SignalState.hpp ------------------------------*- C++ -*-===//
 //
 //                                 The RoSA Framework
 //
 //===----------------------------------------------------------------------===//
 ///
 /// \file rosa/agent/SignalState.hpp
 ///
 /// \author Maximilian Götzinger (maximilian.goetzinger@tuwien.ac.at)
 ///
 /// \date 2019
 ///
 /// \brief Definition of *signal state* *functionality*.
 ///
 //===----------------------------------------------------------------------===//
 
 #ifndef ROSA_AGENT_SIGNALSTATE_HPP
 #define ROSA_AGENT_SIGNALSTATE_HPP
 
 #include "rosa/agent/DistanceMetrics.hpp"
 #include "rosa/agent/FunctionAbstractions.hpp"
 #include "rosa/agent/Functionality.h"
 #include "rosa/agent/History.hpp"
 #include "rosa/agent/State.hpp"
 
 #include "rosa/support/math.hpp"
 
 namespace rosa {
 namespace agent {
 
 /// Signal properties defining the properties of the signal which is monitored
 /// by \c rosa::agent::SignalStateDetector and is saved in \c
 /// rosa::agent::SignalStateInformation.
 enum SignalProperties : uint8_t {
   INPUT = 0, ///< The signal is an input signal
   OUTPUT = 1 ///< The signal is an output signal
 };
 
 /// TODO: write description
 template <typename CONFDATATYPE>
 struct SignalStateInformation : StateInformation<CONFDATATYPE> {
   // Make sure the actual type arguments are matching our expectations.
   STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
                 "confidence type is not to arithmetic");
 
   /// ConfidenceOfMatchingState is the confidence how good the new sample
   /// matches the state.
   CONFDATATYPE ConfidenceOfMatchingState;
 
   /// ConfidenceOfMatchingState is the confidence how bad the new sample
   /// matches the state.
   CONFDATATYPE ConfidenceOfMismatchingState;
 
   /// The SignalProperty saves whether the monitored signal is an input our
   /// output signal.
   SignalProperties SignalProperty;
 
   /// The SignalStateIsValid saves the number of samples which have been
   /// inserted into the state after entering it.
   uint32_t NumberOfInsertedSamplesAfterEntrance;
 
 public:
   SignalStateInformation(unsigned int SignalStateID,
                          SignalProperties _SignalProperty) {
     this->StateID = SignalStateID;
     this->SignalProperty = _SignalProperty;
     this->StateCondition = StateConditions::UNKNOWN;
     this->NumberOfInsertedSamplesAfterEntrance = 0;
     this->StateIsValid = false;
     this->StateJustGotValid = false;
     this->StateIsValidAfterReentrance = false;
     this->ConfidenceStateIsValid = 0;
     this->ConfidenceStateIsInvalid = 0;
     this->ConfidenceStateIsStable = 0;
     this->ConfidenceStateIsDrifting = 0;
   }
 
   SignalStateInformation() = default;
 };
 
 /// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
 /// data in that the confidence values are given, \tparam PROCDATATYPE type of
 /// the relative distance and the type of data in which DABs are saved.
 template <typename INDATATYPE, typename CONFDATATYPE, typename PROCDATATYPE>
 class SignalState : public Functionality {
 
   // Make sure the actual type arguments are matching our expectations.
   STATIC_ASSERT((std::is_arithmetic<INDATATYPE>::value),
                 "input data type not arithmetic");
   STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
                 "confidence data type is not to arithmetic");
   STATIC_ASSERT(
       (std::is_arithmetic<PROCDATATYPE>::value),
       "process data type (DAB and Relative Distance) is not to arithmetic");
 
 public:
   // The metric to calculate the distance between two points
   using DistanceMetricAbstraction =
       Abstraction<std::pair<INDATATYPE, INDATATYPE>, PROCDATATYPE> &;
   // For the convinience to write a shorter data type name
   using PartFuncReference = PartialFunction<INDATATYPE, CONFDATATYPE> &;
   // using PartFuncReference2 = ;
   using StepFuncReference = StepFunction<INDATATYPE, CONFDATATYPE> &;
 
 private:
   /// SignalStateInfo is a struct of SignalStateInformation that contains
   /// information about the current signal state.
   SignalStateInformation<CONFDATATYPE> SignalStateInfo;
 
   /// The metric to calculate the distance between two points
   DistanceMetricAbstraction DistanceMetric;
 
   /// The FuzzyFunctionSampleMatches is the fuzzy function that gives the
   /// confidence how good the new sample matches another sample in the sample
   /// history.
   PartFuncReference FuzzyFunctionSampleMatches;
 
   /// The FuzzyFunctionSampleMismatches is the fuzzy function that gives the
   /// confidence how bad the new sample matches another sample in the sample
   /// history.
   PartFuncReference FuzzyFunctionSampleMismatches;
 
   /// The FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
   /// confidence how many samples from the sampe history match the new sample.
   StepFuncReference FuzzyFunctionNumOfSamplesMatches;
 
   /// The FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives
   /// the confidence how many samples from the sampe history mismatch the new
   /// sample.
   StepFuncReference FuzzyFunctionNumOfSamplesMismatches;
 
   /// The FuzzyFunctionSampleValid is the fuzzy function that gives the
   /// confidence how good one matches another sample in the sample
   /// history. This is done to evaluate whether a state is valid.
   PartFuncReference FuzzyFunctionSampleValid;
 
   /// The FuzzyFunctionSampleInvalid is the fuzzy function that gives the
   /// confidence how bad one sample matches another sample in the sample
   /// history. This is done to evaluate whether a state is invalid.
   PartFuncReference FuzzyFunctionSampleInvalid;
 
   /// The FuzzyFunctionNumOfSamplesValid is the fuzzy function that gives the
   /// confidence how many samples from the sample history match another sample.
   /// This is done to evaluate whether a state is valid.
   StepFuncReference FuzzyFunctionNumOfSamplesValid;
 
   /// The FuzzyFunctionNumOfSamplesInvalid is the fuzzy function that gives
   /// the confidence how many samples from the sample history mismatch another
   /// sample. This is done to evaluate whether a state is invalid.
   StepFuncReference FuzzyFunctionNumOfSamplesInvalid;
 
   /// The FuzzyFunctionSignalIsDrifting is the fuzzy function that gives the
   /// confidence how likely it is that the signal (resp. the state of a signal)
   /// is drifting.
   PartFuncReference FuzzyFunctionSignalIsDrifting;
 
   /// The FuzzyFunctionSignalIsStable is the fuzzy function that gives the
   /// confidence how likely it is that the signal (resp. the state of a signal)
   /// is stable (not drifting).
   PartFuncReference FuzzyFunctionSignalIsStable;
 
   /// TODO: description
   PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionLookBack;
   /// TODO: description
   PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionHistoryDesicion;
   /// TODO: description
   uint32_t DriftLookbackRange;
 
   /// SampleHistory is a history in that the last sample values are stored.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO> SampleHistory;
   /// DAB is a (usually) small history of the last sample values of which a
   /// average is calculated if the DAB is full.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF> DAB;
   /// DABHistory is a history in that the last DABs (to be exact, the averages
   /// of the last DABs) are stored.
   DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO> DABHistory;
 
   /// LowestConfidenceMatchingHistory is a history in that the lowest confidence
   /// for the current sample matches all history samples are saved.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO>
       LowestConfidenceMatchingHistory;
   /// HighestConfidenceMatchingHistory is a history in that the highest
   /// confidence for the current sample matches all history samples are saved.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO>
       HighestConfidenceMismatchingHistory;
 
   /// TempConfidenceMatching is the confidence how good a sample matches the
   /// state. However, the value of this variable is only needed temporarly.
   CONFDATATYPE TempConfidenceMatching = 0;
 
   /// TempConfidenceMatching is the confidence how bad a sample matches the
   /// state. However, the value of this variable is only needed temporarly.
   CONFDATATYPE TempConfidenceMismatching = 0;
 
 public:
   /// Creates an instance by setting all parameters
   /// \param SignalStateID The Id of the SignalStateinfo \c
   /// SignalStateInformation.
   ///
   /// \param DistanceMetric the distance metric to calculate the distance
   /// between two points
   ///
   /// \param FuzzyFunctionSampleMatches The FuzzyFunctionSampleMatches is the
   /// fuzzy function that gives the confidence how good the new sample matches
   /// another sample in the sample history.
   ///
   /// \param FuzzyFunctionSampleMismatches The FuzzyFunctionSampleMismatches is
   /// the fuzzy function that gives the confidence how bad the new sample
   /// matches another sample in the sample history.
   ///
   /// \param FuzzyFunctionNumOfSamplesMatches The
   /// FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
   /// confidence how many samples from the sampe history match the new sample.
   ///
   /// \param FuzzyFunctionNumOfSamplesMismatches The
   /// FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives the
   /// confidence how many samples from the sampe history mismatch the new
   /// sample.
   ///
   /// \param FuzzyFunctionSignalIsDrifting The FuzzyFunctionSignalIsDrifting is
   /// the fuzzy function that gives the confidence how likely it is that the
   /// signal (resp. the state of a signal) is drifting.
   ///
   /// \param FuzzyFunctionSignalIsStable The FuzzyFunctionSignalIsStable is the
   /// fuzzy function that gives the confidence how likely it is that the signal
   /// (resp. the state of a signal) is stable (not drifting).
   ///
   /// \param SampleHistorySize Size of the Sample History \c
   /// DynamicLengthHistory . SampleHistory is a history in that the last sample
   /// values are stored.
   ///
   /// \param DABSize Size of DAB \c DynamicLengthHistory . DAB is a (usually)
   /// small history of the last sample values of which a average is calculated
   /// if the DAB is full.
   ///
   /// \param DABHistorySize Size of the DABHistory \c DynamicLengthHistory .
   /// DABHistory is a history in that the last DABs (to be exact, the averages
   /// of the last DABs) are stored.
   ///
   SignalState(
       uint32_t SignalStateID, SignalProperties SignalProperty,
       uint32_t SampleHistorySize, uint32_t DABSize, uint32_t DABHistorySize,
       DistanceMetricAbstraction DistanceMetric,
       PartFuncReference FuzzyFunctionSampleMatches,
       PartFuncReference FuzzyFunctionSampleMismatches,
       StepFuncReference FuzzyFunctionNumOfSamplesMatches,
       StepFuncReference FuzzyFunctionNumOfSamplesMismatches,
       PartFuncReference FuzzyFunctionSampleValid,
       PartFuncReference FuzzyFunctionSampleInvalid,
       StepFuncReference FuzzyFunctionNumOfSamplesValid,
       StepFuncReference FuzzyFunctionNumOfSamplesInvalid,
       // SAVE CHANGES
       PartFuncReference FuzzyFunctionSignalIsDrifting,
       PartFuncReference FuzzyFunctionSignalIsStable,
       PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionLookBack,
       // - SAVE CHANGES
       PartialFunction<uint32_t, float>
           &FuzzyFunctionSignalConditionHistoryDesicion,
       uint32_t DriftLookbackRange) noexcept
       : SignalStateInfo{SignalStateID, SignalProperty},
         DistanceMetric(DistanceMetric),
         FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
         FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
         FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
         FuzzyFunctionNumOfSamplesMismatches(
             FuzzyFunctionNumOfSamplesMismatches),
         FuzzyFunctionSampleValid(FuzzyFunctionSampleValid),
         FuzzyFunctionSampleInvalid(FuzzyFunctionSampleInvalid),
         FuzzyFunctionNumOfSamplesValid(FuzzyFunctionNumOfSamplesValid),
         FuzzyFunctionNumOfSamplesInvalid(FuzzyFunctionNumOfSamplesInvalid),
         FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
         FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable),
         // SAVE CHANGES
         FuzzyFunctionSignalConditionLookBack(
             FuzzyFunctionSignalConditionLookBack),
         FuzzyFunctionSignalConditionHistoryDesicion(
             FuzzyFunctionSignalConditionHistoryDesicion),
         DriftLookbackRange(DriftLookbackRange),
         // - SAVE CHANGES
         SampleHistory(SampleHistorySize), DAB(DABSize),
         DABHistory(DABHistorySize),
         LowestConfidenceMatchingHistory(SampleHistorySize),
         HighestConfidenceMismatchingHistory(SampleHistorySize) {}
 
   /// Destroys \p this object.
   ~SignalState(void) = default;
 
   void leaveSignalState(void) noexcept {
     DAB.clear();
     SignalStateInfo.NumberOfInsertedSamplesAfterEntrance = 0;
     SignalStateInfo.StateIsValidAfterReentrance = false;
   }
 
   SignalStateInformation<CONFDATATYPE>
   insertSample(INDATATYPE Sample) noexcept {
 
     SignalStateInfo.NumberOfInsertedSamplesAfterEntrance++;
 
     validateSignalState(Sample);
 
     SampleHistory.addEntry(Sample);
 
     DAB.addEntry(Sample);
     if (DAB.full()) {
 
       // TODO: make soring inside of median
       // TODO: make better outlier removal!
       // std::sort(DAB.begin(), DAB.end());
       // DAB.erase(DAB.begin(), DAB.begin() + 1);
       // DAB.erase(DAB.end() - 1, DAB.end());
       // PROCDATATYPE AvgOfDAB = DAB.template median<PROCDATATYPE>();
-      PROCDATATYPE AvgOfDAB = DAB.template average<PROCDATATYPE>();
+      PROCDATATYPE AvgOfDAB = DAB.template median<PROCDATATYPE>();
 
       DABHistory.addEntry(AvgOfDAB);
       DAB.clear();
     }
 
     FuzzyFunctionNumOfSamplesMatches.setRightLimit(
         static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
     FuzzyFunctionNumOfSamplesMismatches.setRightLimit(
         static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
 
     checkSignalStability();
 
     SignalStateInfo.ConfidenceOfMatchingState = TempConfidenceMatching;
     SignalStateInfo.ConfidenceOfMismatchingState = TempConfidenceMismatching;
 
     return SignalStateInfo;
   }
 
   /// Gives the confidence how likely the new sample matches the signal state.
   ///
   /// \param Sample is the actual sample of the observed signal.
   ///
   /// \return the confidence of the new sample is matching the signal state.
   CONFDATATYPE
   confidenceSampleMatchesSignalState(INDATATYPE Sample) noexcept {
 
     CONFDATATYPE ConfidenceOfBestCase = 0;
 
     DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::FIFO>
         RelativeDistanceHistory(SampleHistory.maxLength());
 
     // Calculate distances to all history samples.
     for (auto &HistorySample : SampleHistory) {
       PROCDATATYPE RelativeDistance =
           DistanceMetric(std::make_pair(Sample, HistorySample));
       RelativeDistanceHistory.addEntry(RelativeDistance);
     }
 
     // Sort all calculated distances so that the lowest distance (will get the
     // highest confidence) is at the beginning.
     RelativeDistanceHistory.sortAscending();
 
     CONFDATATYPE ConfidenceOfWorstFittingSample = 1;
 
     // Case 1 means that one (the best fitting) sample of the history is
     // compared with the new sample. Case 2 means the two best history samples
     // are compared with the new sample. And so on.
     // TODO (future): to accelerate . don't start with 1 start with some higher
     // number because a low number (i guess lower than 5) will definetely lead
     // to a low confidence. except the history is not full.
 
     // Case 1 means that one (the best fitting) sample of the history is
     // compared with the new sample. Case 2 means the two best history samples
     // are compared with the new sample. And so on.
     for (uint32_t Case = 0; Case < RelativeDistanceHistory.numberOfEntries();
          Case++) {
 
       CONFDATATYPE ConfidenceFromRelativeDistance;
 
       if (std::isinf(RelativeDistanceHistory[Case])) {
         // TODO (future): if fuzzy is defined in a way that infinity is not 0 it
         // would be a problem.
         ConfidenceFromRelativeDistance = 0;
       } else {
         ConfidenceFromRelativeDistance =
             FuzzyFunctionSampleMatches(RelativeDistanceHistory[Case]);
       }
       ConfidenceOfWorstFittingSample = fuzzyAND(ConfidenceOfWorstFittingSample,
                                                 ConfidenceFromRelativeDistance);
 
       ConfidenceOfBestCase =
           fuzzyOR(ConfidenceOfBestCase,
                   fuzzyAND(ConfidenceOfWorstFittingSample,
                            FuzzyFunctionNumOfSamplesMatches(
                                static_cast<CONFDATATYPE>(Case) + 1)));
     }
 
     TempConfidenceMatching = ConfidenceOfBestCase;
 
     return ConfidenceOfBestCase;
   }
 
   /// Gives the confidence how likely the new sample mismatches the signal
   /// state.
   ///
   /// \param Sample is the actual sample of the observed signal.
   ///
   /// \return the confidence of the new sample is mismatching the signal state.
   CONFDATATYPE
   confidenceSampleMismatchesSignalState(INDATATYPE Sample) noexcept {
 
     float ConfidenceOfWorstCase = 1;
 
     DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::FIFO>
         RelativeDistanceHistory(SampleHistory.maxLength());
 
     // Calculate distances to all history samples.
     for (auto &HistorySample : SampleHistory) {
       RelativeDistanceHistory.addEntry(
           DistanceMetric(std::make_pair(Sample, HistorySample)));
     }
 
     // Sort all calculated distances so that the highest distance (will get the
     // lowest confidence) is at the beginning.
     RelativeDistanceHistory.sortDescending();
 
     CONFDATATYPE ConfidenceOfBestFittingSample = 0;
 
     // TODO (future): to accelerate -> don't go until end. Confidences will only
     // get higher. See comment in "CONFDATATYPE
     // confidenceSampleMatchesSignalState(INDATATYPE Sample)".
 
     // Case 1 means that one (the worst fitting) sample of the history is
     // compared with the new sample. Case 2 means the two worst history samples
     // are compared with the new sample. And so on.
     for (uint32_t Case = 0; Case < RelativeDistanceHistory.numberOfEntries();
          Case++) {
 
       CONFDATATYPE ConfidenceFromRelativeDistance;
 
       if (std::isinf(RelativeDistanceHistory[Case])) {
         ConfidenceFromRelativeDistance = 1;
       } else {
         ConfidenceFromRelativeDistance =
             FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]);
       }
 
       ConfidenceOfBestFittingSample = fuzzyOR(ConfidenceOfBestFittingSample,
                                               ConfidenceFromRelativeDistance);
 
       ConfidenceOfWorstCase =
           fuzzyAND(ConfidenceOfWorstCase,
                    fuzzyOR(ConfidenceOfBestFittingSample,
                            FuzzyFunctionNumOfSamplesMismatches(
                                static_cast<CONFDATATYPE>(Case) + 1)));
     }
 
     TempConfidenceMismatching = ConfidenceOfWorstCase;
 
     return ConfidenceOfWorstCase;
   }
 
   /// Gives information about the current signal state.
   ///
   /// \return a struct SignalStateInformation that contains information about
   /// the current signal state.
   SignalStateInformation<CONFDATATYPE> signalStateInformation(void) noexcept {
     return SignalStateInfo;
   }
 
 private:
   void validateSignalState(INDATATYPE Sample) {
     // TODO (future): WorstConfidenceDistance and BestConfidenceDistance could
     // be set already in "CONFDATATYPE
     // confidenceSampleMatchesSignalState(INDATATYPE Sample)" and "CONFDATATYPE
     // confidenceSampleMismatchesSignalState(INDATATYPE Sample)" when the new
     // sample is compared to all history samples. This would save a lot time
     // because the comparisons are done only once. However, it has to be asured
     // that the these two functions are called before the insertation, and the
     // FuzzyFunctions for validation and matching have to be the same!
     CONFDATATYPE LowestConfidenceMatching = 1;
     CONFDATATYPE HighestConfidenceMismatching = 0;
 
     for (auto &HistorySample : SampleHistory) {
       // TODO (future): think about using different fuzzy functions for
       // validation and matching.
       LowestConfidenceMatching =
           fuzzyAND(LowestConfidenceMatching,
                    FuzzyFunctionSampleMatches(
                        DistanceMetric(std::make_pair(Sample, HistorySample))));
 
       HighestConfidenceMismatching =
           fuzzyOR(HighestConfidenceMismatching,
                   FuzzyFunctionSampleMismatches(
                       DistanceMetric(std::make_pair(Sample, HistorySample))));
     }
     LowestConfidenceMatchingHistory.addEntry(LowestConfidenceMatching);
     HighestConfidenceMismatchingHistory.addEntry(HighestConfidenceMismatching);
 
     LowestConfidenceMatching = LowestConfidenceMatchingHistory.lowestEntry();
     HighestConfidenceMismatching =
         HighestConfidenceMismatchingHistory.highestEntry();
 
     SignalStateInfo.ConfidenceStateIsValid =
         fuzzyAND(LowestConfidenceMatching,
                  FuzzyFunctionNumOfSamplesValid(static_cast<INDATATYPE>(
                      SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));
 
     SignalStateInfo.ConfidenceStateIsInvalid =
         fuzzyOR(HighestConfidenceMismatching,
                 FuzzyFunctionNumOfSamplesInvalid(static_cast<INDATATYPE>(
                     SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));
 
     if (SignalStateInfo.ConfidenceStateIsValid >
         SignalStateInfo.ConfidenceStateIsInvalid) {
 
       if (SignalStateInfo.StateIsValid) {
         SignalStateInfo.StateJustGotValid = false;
       } else {
         SignalStateInfo.StateJustGotValid = true;
       }
 
       SignalStateInfo.StateIsValid = true;
       SignalStateInfo.StateIsValidAfterReentrance = true;
     }
   }
 
   void checkSignalStability(void) {
 
     /*
   std::cout << "LookbackTest: " << std::endl;
   for (unsigned int t = 1; t <= DriftLookbackRange + 5; t++) {
     std::cout << "t=" << t
               << " -> c=" << FuzzyFunctionSignalConditionLookBack(t)
               << std::endl;
 
     //(*FuzzyFunctionTimeSystemFunctioning)(
     // static_cast<INDATATYPE>(TimeOfDisparity));
   }
   getchar();
 */
     SignalStateInfo.ConfidenceStateIsStable = 0;
     SignalStateInfo.ConfidenceStateIsDrifting = 0;
 
     /*
     std::cout << "ConfidenceStateIsStable (before): "
               << SignalStateInfo.ConfidenceStateIsStable << std::endl;
     std::cout << "ConfidenceStateIsDrifting (before): "
               << SignalStateInfo.ConfidenceStateIsDrifting << std::endl;
 */
 
     bool DriftDirectionIsUp = true;
 
     if (DABHistory.numberOfEntries() >= 2) {
 
       // SAVE CHANGES
       INDATATYPE CurrentDAB = DABHistory[DABHistory.numberOfEntries() - 1];
       INDATATYPE DAB2Compare = DABHistory[0];
 
       // ########### TODO HERE: calculating up_down
 
       uint32_t DriftDnCounter = 0;
       uint32_t DriftUpCounter = 0;
 
       // EXPERIMENTING
       for (unsigned int t = 1;
            t <= DriftLookbackRange && t < DABHistory.numberOfEntries(); t++) {
 
         DAB2Compare = DABHistory[DABHistory.numberOfEntries() - (t + 1)];
 
         // TODO: make the following also for distance measurement when comparing
         // sample with state and validate state
         /*
         // sigma correction
         if (NormalizedDistanceMetric<INDATATYPE, PROCDATATYPE>
                 *NormalizableDistanceMetric = dynamic_cast<
                     NormalizedDistanceMetric<INDATATYPE, PROCDATATYPE> *>(
                     DistanceMetric)) {
           // old was safely casted to NewType
           NormalizableDistanceMetric->setNorm(
               // TODO: (1) Sigma von Sample
               // History(!) abholen, (2) irgendwas mit Sigma hier reinschreiben,
               // und (3) überlegen wegen zweiter History (länger) für
               // Sigmaberechnung
           );
         }
        */
 
         float dist = DistanceMetric(std::make_pair(CurrentDAB, DAB2Compare));
 
         // AVG
         SignalStateInfo.ConfidenceStateIsStable +=
             FuzzyFunctionSignalIsStable(dist);
         SignalStateInfo.ConfidenceStateIsDrifting +=
             FuzzyFunctionSignalIsDrifting(dist);
         // TODO: move following outside of the loop with
         // "if(DriftLookbackRange<=DABHistory.numberOfEntries())"
         if (t == DriftLookbackRange) {
           SignalStateInfo.ConfidenceStateIsStable /= DriftLookbackRange;
           SignalStateInfo.ConfidenceStateIsDrifting /= DriftLookbackRange;
         } else if (t == DABHistory.numberOfEntries() - 1) {
           SignalStateInfo.ConfidenceStateIsStable /=
               DABHistory.numberOfEntries();
           SignalStateInfo.ConfidenceStateIsDrifting /=
               DABHistory.numberOfEntries();
         }
 
         /*
         // AND
         SignalStateInfo.ConfidenceStateIsStable =
             fuzzyOR(SignalStateInfo.ConfidenceStateIsStable,
                     fuzzyAND(FuzzyFunctionSignalIsStable(dist),
                              FuzzyFunctionSignalConditionLookBack(t)));
 
         SignalStateInfo.ConfidenceStateIsDrifting =
             fuzzyOR(SignalStateInfo.ConfidenceStateIsDrifting,
                     fuzzyAND(FuzzyFunctionSignalIsDrifting(dist),
                              FuzzyFunctionSignalConditionLookBack(t)));
         */
         /*
         // MULTI
         SignalStateInfo.ConfidenceStateIsStable =
             fuzzyOR(SignalStateInfo.ConfidenceStateIsStable,
                     FuzzyFunctionSignalIsStable(
                         relativeDistance<INDATATYPE, PROCDATATYPE>(
                             CurrentDAB, DAB2Compare)) *
                         FuzzyFunctionSignalConditionLookBack(t));
 
         SignalStateInfo.ConfidenceStateIsDrifting =
             fuzzyOR(SignalStateInfo.ConfidenceStateIsDrifting,
                     FuzzyFunctionSignalIsDrifting(
                         relativeDistance<INDATATYPE, PROCDATATYPE>(
                             CurrentDAB, DAB2Compare)) *
                         FuzzyFunctionSignalConditionLookBack(t));
         */
 
         if (CurrentDAB > DAB2Compare)
           DriftUpCounter++;
         else if (CurrentDAB < DAB2Compare)
           DriftDnCounter++;
       }
       // TODO: change something because it is biased if the are equal
       DriftDirectionIsUp = DriftUpCounter > DriftDnCounter;
 
       // following outcommented block was the published code
       /*
           SignalStateInfo.ConfidenceStateIsStable =
           FuzzyFunctionSignalIsStable(
               relativeDistance<INDATATYPE, PROCDATATYPE>(CurrentDAB,
                                                          DAB2Compare));
       SignalStateInfo.ConfidenceStateIsDrifting =
           FuzzyFunctionSignalIsDrifting(
               relativeDistance<INDATATYPE, PROCDATATYPE>(CurrentDAB,
                                                          DAB2Compare));
       // TODO: think about a better solution with different confidences
       // (stable, up, down, ...)
       DriftDirectionIsUp = CurrentDAB > DAB2Compare;
       */
       // - SAVE CHANGES
     }
 
     /*
     std::cout << "ConfidenceStateIsStable (after): "
               << SignalStateInfo.ConfidenceStateIsStable << std::endl;
     std::cout << "ConfidenceStateIsDrifting (after): "
               << SignalStateInfo.ConfidenceStateIsDrifting << std::endl;
   */
 
     if (SignalStateInfo.ConfidenceStateIsStable >
         SignalStateInfo.ConfidenceStateIsDrifting) {
       SignalStateInfo.StateCondition = StateConditions::STABLE;
     } else if (SignalStateInfo.ConfidenceStateIsStable <
                SignalStateInfo.ConfidenceStateIsDrifting) {
 
       if (DriftDirectionIsUp) {
         SignalStateInfo.StateCondition = StateConditions::DRIFTING_UP;
       } else {
         SignalStateInfo.StateCondition = StateConditions::DRIFTING_DN;
       }
       /*
         SignalStateInfo.StateCondition = StateConditions::DRIFTING;
         */
     } else {
       SignalStateInfo.StateCondition = StateConditions::UNKNOWN;
     }
   }
 }; // namespace agent
 
 } // namespace agent
 } // End namespace rosa
 
 #endif // ROSA_AGENT_SIGNALSTATE_HPP