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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......................32 8........................................................................................................................................1 Fuzzy Neural Networks ..............................29 6.............................................................14 3.........................................................................................................................4 Artificial neural networks ............ THE SIMULATION ......................................1 Network parameters .................TABLE CONTENTS LIST FIGURES LIST TABLES 1.........................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ...24 5.............................................................2 2....1...28 6........................30 7..........................................................................................................................9 3.....1.........43 8.............................................................1 The basic Artificial Neuron..................................... INTRODUCTION ........40 8...............................................................................................................................17 4........... BACKPROPAGATION ALGORITHM ...2 The ANFIS network........................ NEURAL NETWORKS...................22 5.......................................................1 The algorithm .....................................................................................................................17 5..........................1 Network parameters ............................................1.....1 Real brains....................4....................................50 LIST INSERTS ................................2 Operation neurons....................................................3 Learning ..1 Description the backpropagation algorithm..........22 5...................................................2 Analysis using filter banks ..40 8....................1...........................................................6 3............................................................................................43 8......................................... CONCLUSION........1 Forward pass...............2 Backward pass ..................1 Division into frames and preprocessing .............................................46 REFERENCES ........................................................................................43 9..................................................................37 8....1 Learning algorithm ANFIS ...................................3 Stop the training ..............................1 Signal preparation ..................29 6.2..................................51 .......................2..............2 2..........................................9 3...................................................................5 2................................................................................ THE REALIZATION THE PROGRAM...............................................................1.................................................4 2.........................................................40 8.............................................15 4....................................1........................................2 Running the algorithm ...................................................................................26 6.....................................................2 Running the simulation .................................................................... THE SPEECH SIGNAL .................12 3................................................5 2..............................2 Simulation results ................................................................. ADAPTIVE NEURO FUZZY INFERENCE SYSTEM................................ FUZZY SYSTEMS ................................................1 2........................................................................................................1...........................................................1 The 'NNV' network....................

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