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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.......40 8.........................37 8..................................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES .................................................................................26 6........1 The basic Artificial Neuron.............2 Analysis using filter banks .4 2..........22 5..1 Learning algorithm ANFIS .......................................................22 5....................................................4...1 The algorithm ........1.............................1 Real brains......................9 3...2 Backward pass ..........2 The ANFIS network...............................................................................................................................................................................1........... THE SIMULATION .........................................................................................................................................3 Learning .....................................................2 Operation neurons......................... THE SPEECH SIGNAL ..................43 9................................................................................................................................1 Description the backpropagation algorithm................46 REFERENCES .....................................1...........32 8.............................................................1 2...................................................................................................................................................... CONCLUSION......................................................... FUZZY SYSTEMS ..40 8.............................................................................2 2..1.... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM............ BACKPROPAGATION ALGORITHM .............................................................1..........................40 8..1 Signal preparation ............................................14 3........................................................................1 The 'NNV' network...................................6 3............................................1 Network parameters ....................................................................................17 5................................................................TABLE CONTENTS LIST FIGURES LIST TABLES 1...........................................................................................................................30 7................2........................................ NEURAL NETWORKS..........2 Running the algorithm ...............15 4.....29 6.................................................................................................5 2.....................4 Artificial neural networks ................................................................................2 Running the simulation ............................................................................................................................................29 6...................................1 Forward pass....................................1........................ INTRODUCTION .....................................................................24 5...........50 LIST INSERTS ....43 8.........1 Network parameters ......2...............................................51 ................................................................................................1............................................17 4......................................................... THE REALIZATION THE PROGRAM.........43 8..............................................................1 Fuzzy Neural Networks .................................................................................5 2..........................................................................12 3.3 Stop the training .......2 2......................................9 3......2 Simulation results .................................1 Division into frames and preprocessing .............................................28 6........................................

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