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

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