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

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