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 Operation neurons........................................................................................................................14 3.................1 Fuzzy Neural Networks .....6 3..........................................................1..........................................1 The 'NNV' network........................................................40 8........................................22 5.......................................1 Description the backpropagation algorithm...............................................................................................2 Simulation results ...............................................................................................................................9 3...................................................................................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ..............................................2 Running the simulation ..................................................2 Backward pass ....................................................................................................................................................................................................1 Learning algorithm ANFIS ............................................................... THE SPEECH SIGNAL .................... INTRODUCTION ......................................................4 Artificial neural networks ....1.........................................................30 7...................................................29 6...................... BACKPROPAGATION ALGORITHM ......2 The ANFIS network..................1 2......... THE REALIZATION THE PROGRAM........... NEURAL NETWORKS......43 9..............32 8.....................43 8...............................................1 Network parameters ......................................................................29 6...........................................1......................................................1 Forward pass........................1 Network parameters ................................TABLE CONTENTS LIST FIGURES LIST TABLES 1....................5 2...........................................................................................................46 REFERENCES ....43 8..................................................................................1....................................................................................................................... FUZZY SYSTEMS ........24 5.............................................................................................. THE SIMULATION ... CONCLUSION........2 2............1........................................1 The basic Artificial Neuron.....................40 8..................17 5.............................................................................2...28 6...................26 6...12 3.............................................3 Learning ......................................3 Stop the training ......17 4.................................................................1 Real brains........2 Running the algorithm .........1 Division into frames and preprocessing ................9 3...4......50 LIST INSERTS ...5 2...............................1 Signal preparation .....................................37 8...............................22 5......... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM...2 2................15 4.......1......................................................................................................................................................................................................................................................2 Analysis using filter banks ...........................................1 The algorithm ....40 8...51 .......................................................................................4 2.1............................2........................................................................................................................................................

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