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

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