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

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