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

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