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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...............................................1 Fuzzy Neural Networks ....43 8....................................1.................1 Real brains. INTRODUCTION ..........................................5 2.....15 4.........................................2 Running the algorithm .................................................1 The algorithm ..............................................................................................2 Simulation results ...........................................................................................................................................................5 2............................................................................................................................................................................2 Operation neurons..... BACKPROPAGATION ALGORITHM ........................................17 4.................................................1 Description the backpropagation algorithm...............2..............................................................................29 6....................43 8.......................................................................4 2..............................1 Forward pass................................2 Analysis using filter banks .................................................................2 Backward pass ....................................1..2 2...................................................................................40 8........26 6...............................29 6..........................................................................................1 The basic Artificial Neuron....2....................................2 2........1 Division into frames and preprocessing .......................1 Learning algorithm ANFIS .........................32 8...................................................................... FUZZY SYSTEMS ............1 2..........................24 5...................................30 7...4.......................TABLE CONTENTS LIST FIGURES LIST TABLES 1.............................................40 8...................................14 3.6 3.....................1.....40 8....................................1 The 'NNV' network................... THE SPEECH SIGNAL ..................................................................2 The ANFIS network...................................................................22 5............1 Signal preparation ...............................................................................................................22 5.......................................................................................9 3..........................51 ......................................................................................................1 Network parameters ...............................1.........................................................................................................................2 Running the simulation ...................................................3 Stop the training ..........................4 Artificial neural networks ...... CONCLUSION...........................1................................................................................37 8....1.............................................................................................1.......9 3...... THE SIMULATION .......43 9....................................................................... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM...................3 Learning .....1 Network parameters .............................................................................................................................12 3......28 6................................................ THE REALIZATION THE PROGRAM.................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ...................................................................................................................................... NEURAL NETWORKS.......17 5...50 LIST INSERTS ............................46 REFERENCES ..............................

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