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 Network parameters ............................................................................................................... FUZZY SYSTEMS ........2 Analysis using filter banks ............37 8...............................................................29 6.........1.........28 6.......................................................................................................................................................................................................1 Network parameters ...............................................................................1 Learning algorithm ANFIS ..46 REFERENCES .51 ....................................................................3 Learning ...........................4 2.............................1.....................1 Forward pass................................................................................1 Signal preparation .................................40 8.......9 3........................17 5...............................................................43 9..........................................1..24 5........ BACKPROPAGATION ALGORITHM .......................15 4..............2 Operation neurons...1 2.............................................4...........................................................1 The basic Artificial Neuron.......................50 LIST INSERTS ...............1 Fuzzy Neural Networks ...................2 Running the algorithm ....................................................................................................1 Real brains.........................................................................................................17 4..........................................................2 2..................... CONCLUSION...........................6 3................................................ THE REALIZATION THE PROGRAM.......................................................................................................1.................................................... NEURAL NETWORKS...................................................................................... INTRODUCTION ...............................................................................2 Simulation results ................................................................................2........................................9 3...........................26 6.............................2 Running the simulation ........ THE SPEECH SIGNAL ...............................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ......43 8.1................................................................................................1.....5 2.................................14 3.... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM.............29 6.................22 5................................40 8.....................1 The 'NNV' network.............................................40 8..................................2 Backward pass ................................................................................................................... THE SIMULATION ........30 7.........1 Division into frames and preprocessing ..........................................................................................................................................2.................1 The algorithm ............................TABLE CONTENTS LIST FIGURES LIST TABLES 1.............................................................4 Artificial neural networks ..........................32 8...............12 3.........................................................43 8................................................3 Stop the training .....2 2..1 Description the backpropagation algorithm........2 The ANFIS network.....................................5 2......................................................................................1...............22 5................................................................................................................................................................

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