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 The 'NNV' network.......17 5.................................1............................50 LIST INSERTS .........2 The ANFIS network.............................................................................................................1 Description the backpropagation algorithm..4 Artificial neural networks ..............................................3 Stop the training ....................................1 Network parameters .........................................................................................................................1 The basic Artificial Neuron..................................................................30 7......................3 Learning ......................................................1 Division into frames and preprocessing .....................................................2 Running the algorithm ............2 Backward pass ............1 Forward pass...............................1......................................................1 2...........................................32 8...............................................29 6.................................46 REFERENCES ..........................................................14 3..................................2 2...........................17 4.......................................TABLE CONTENTS LIST FIGURES LIST TABLES 1..................37 8...................................... NEURAL NETWORKS........................................22 5...........................1 Learning algorithm ANFIS ...43 8...43 9..40 8..................9 3............................1 Fuzzy Neural Networks ...........................1......................... CONCLUSION.............5 2....................................................2 Running the simulation .......................................................................28 6.....................................................................................................9 3...........6 3................................................................................1.26 6............................2..................43 8...........4 2...................................... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM......................................................... FUZZY SYSTEMS .....................................1..................................................1......................................................................................................2 2............................................................................................................51 .............................................................5 2..............................................24 5.................................... THE SPEECH SIGNAL ......................15 4............ BACKPROPAGATION ALGORITHM .........................................................40 8............................12 3................40 8.......................................................................1 Real brains...............................................................................................................................2......................................................22 5............. THE SIMULATION ........................................................................................1 The algorithm .......1 Signal preparation ..................................4...............................................................................................................................2 Simulation results .............2 Operation neurons..............................................29 6...48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ....... INTRODUCTION .......................................1..................................................................................................... THE REALIZATION THE PROGRAM..................1 Network parameters ............2 Analysis using filter banks .....................................................................................

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