Klasifikace vzorů pomocí fuzzy neuronových sítí

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Práce popisuje základy principu funkčnosti neuronů a vytvoření umělých neuronových sítí. Je zde důkladně popsána struktura a funkce neuronů a ukázán nejpoužívanější algoritmus pro učení neuronů. Základy fuzzy logiky, včetně jejich výhod a nevýhod, jsou rovněž prezentovány. Detailněji je popsán algoritmus zpětného šíření chyb a adaptivní neuro-fuzzy inferenční systém. Tyto techniky poskytují efektivní způsoby učení neuronových sítí.

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........................................................................................15 4.......................................................2 2.................................................................................................................1 The 'NNV' network..2 Running the simulation ........................................................................................50 LIST INSERTS ............................17 4................. NEURAL NETWORKS.............29 6............30 7..................12 3..................................................................................................... THE REALIZATION THE PROGRAM...37 8.......................1........................................................................................................................................................................................................2 Operation neurons..................................................2..............................................................2 Running the algorithm ................................................................................................................................................................24 5................................................................................................................51 .....................43 8.2 Simulation results .......... CONCLUSION.........................................1...1 Network parameters ....................1 Network parameters ................................................................................... THE SPEECH SIGNAL ............................2 2................................2 Analysis using filter banks ...........1 Forward pass..... INTRODUCTION ..............................................................................................................1 Learning algorithm ANFIS .............................14 3..................................4...............................2...........................................................................................................................................4 Artificial neural networks ........17 5.....................................................TABLE CONTENTS LIST FIGURES LIST TABLES 1..............................5 2...............................................................................28 6.....................................1 The algorithm .............................................................................................................................. ADAPTIVE NEURO FUZZY INFERENCE SYSTEM..............................................................................................1 2............................3 Stop the training ..1.5 2.......................9 3...........................43 8............................22 5......................1 Description the backpropagation algorithm.............................................................40 8.........................................1 Real brains.....2 The ANFIS network.....................1 Fuzzy Neural Networks .....43 9.......................................... FUZZY SYSTEMS .......1..........................................................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES .......40 8...6 3.............................4 2.....................1.....2 Backward pass ........................32 8...............................................26 6...............................1.... THE SIMULATION ...................................................................................9 3......1 Division into frames and preprocessing ............................ BACKPROPAGATION ALGORITHM .................................................................................22 5..........................1......29 6..........................................................................40 8.............................3 Learning ...................46 REFERENCES ..................1 The basic Artificial Neuron...........................................1 Signal preparation ...........................

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