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

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