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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.............................................................2 2...................................3 Stop the training ......................................40 8..............40 8................. THE SPEECH SIGNAL ...........1 2....................................................................................................................1 Forward pass.....................................2...........2 Running the algorithm .............................43 8.................... THE SIMULATION .........3 Learning .....1 Division into frames and preprocessing ............................1..................1 Learning algorithm ANFIS ....................1 Network parameters ..............................28 6...1 Description the backpropagation algorithm........................................................................................................................................................40 8................ FUZZY SYSTEMS ................................................................................................1 Signal preparation ...............26 6........22 5...................37 8.....................................................................................43 9........2 Analysis using filter banks .....................................................................9 3...........5 2............2 Running the simulation .........................................................................4 2..............................................................................17 4........................................................................1 The algorithm .................................1......... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM.................................................................................9 3............................5 2.48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ...............................1 The 'NNV' network.............1 Real brains..................................................................................22 5.......2 The ANFIS network....................................................................................1....................................1...................................................................................................................................................................................................................................................................................................................................... CONCLUSION.43 8......................................................................17 5........................32 8..6 3...............1.....................................4...............................................................................................2 Operation neurons..............................1 Fuzzy Neural Networks .... INTRODUCTION ...................51 ................2....................................................................14 3..................................... THE REALIZATION THE PROGRAM.........1...............12 3................................................................................................................................ BACKPROPAGATION ALGORITHM ...........................15 4...........................................................2 Simulation results .........1 The basic Artificial Neuron..................................................................................................................................................................1.....................................................50 LIST INSERTS ................................................................1 Network parameters .29 6..............................30 7..........2 2..........2 Backward pass .....4 Artificial neural networks .............. NEURAL NETWORKS.............................................................................TABLE CONTENTS LIST FIGURES LIST TABLES 1..........................46 REFERENCES ....................29 6.24 5...................................................................................

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