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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..............................................................................1......................................................................................................................................50 LIST INSERTS ................ FUZZY SYSTEMS ..............................4.............1 Real brains..............................5 2.....................1 The basic Artificial Neuron.......................15 4.................................................................................................................................................................................2 2.................................................... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM..........................................................17 4............1 Network parameters ..............................................................................1.........................3 Learning ........43 8......1............. THE SPEECH SIGNAL .......................................................................2 The ANFIS network............................40 8......................1 The algorithm ......................................................................................................................................2 Operation neurons..1 The 'NNV' network.... INTRODUCTION .........................................................1 Division into frames and preprocessing .............5 2.......3 Stop the training ............................................17 5.......2 Backward pass .....................................TABLE CONTENTS LIST FIGURES LIST TABLES 1. THE REALIZATION THE PROGRAM....................................................4 2.1 Signal preparation ..............................1...............................1 Learning algorithm ANFIS ...............40 8...................................12 3.........2 Analysis using filter banks ........ THE SIMULATION ...............................43 8...........................................................................1 Description the backpropagation algorithm..1 2.............................................................22 5...................1 Fuzzy Neural Networks ..................................1.....................1 Forward pass.......26 6........................................................................... NEURAL NETWORKS..........................................................................................................2 2.............................................................................................................................2 Running the algorithm .............24 5.............................9 3..........................................................................43 9........................1........................................................................2 Running the simulation .2 Simulation results ..........28 6...9 3.............................................................................................1 Network parameters .................................................................37 8..........................................................................................32 8..................................................................2...........................................................14 3...........48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ....51 .......4 Artificial neural networks .......................................................................................................................... CONCLUSION........2............................................................................22 5...... BACKPROPAGATION ALGORITHM ....................................................29 6........................29 6................................................................46 REFERENCES ....6 3...30 7...40 8.................................................................................................................................................................................................................................................1......

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