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 2..........................1 Learning algorithm ANFIS ...........................................1.........................................................................................................5 2..................................................46 REFERENCES .......TABLE CONTENTS LIST FIGURES LIST TABLES 1............................................................... FUZZY SYSTEMS ........................................................................................................................................ BACKPROPAGATION ALGORITHM .................9 3.............40 8............................................1 Real brains............................................................................1..............................1 Fuzzy Neural Networks ................. CONCLUSION.......................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES .....2 Simulation results ...............................................................1..............................................................50 LIST INSERTS .........................................................................................................................................................43 8.......................................................1.......................29 6.................22 5.30 7...............26 6...2 Backward pass ................................................................................15 4................................................................................ ADAPTIVE NEURO FUZZY INFERENCE SYSTEM..................................17 4...................................................................40 8.........1 The 'NNV' network........... THE REALIZATION THE PROGRAM..........................................14 3...... INTRODUCTION ...........................................................................................................................................................22 5...............2 The ANFIS network..................................................................................................1........................ THE SIMULATION ...........................................4........................2....................1...............................................1 Signal preparation ..........................................................9 3...........1 Network parameters ......................51 ...................1 Description the backpropagation algorithm.......................................29 6.....................5 2........2 2.............................................................1 Division into frames and preprocessing .................................................................................................................1 The basic Artificial Neuron.........................................................43 9.................43 8...........2..........................................................1 Network parameters ..................................24 5.... NEURAL NETWORKS................1 Forward pass...........2 Analysis using filter banks ...........................................................................................................28 6..............................................4 Artificial neural networks ................................................................................................................................1.....................................................40 8.....................32 8.............2 Running the simulation ................1 The algorithm .........................3 Learning ............................. THE SPEECH SIGNAL ...........................12 3............................37 8......................................................................4 2......................................3 Stop the training .........................................................................2 Running the algorithm ...............6 3.........................17 5.............................................................1 2.......2 Operation neurons....

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