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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................................................................................................................................................................................46 REFERENCES ...........................................................................15 4.......26 6.........................................................................2 Simulation results ............................................................................................................2 The ANFIS network..............................................................................................1 The 'NNV' network.....40 8......................2 Analysis using filter banks ............2............................................1 The algorithm ..................................................................1..................... CONCLUSION........................................ THE SPEECH SIGNAL ....................................1.......................................3 Stop the training ..............................................................................................22 5....................2 2.........2 Backward pass ..................................................................................17 4........5 2............................1 Division into frames and preprocessing ..................29 6....43 8...............................................................................30 7.......................2 Running the algorithm ......................1............5 2........................................1 Network parameters ....................................22 5...............................37 8........................2 Running the simulation ..................................14 3............1 Forward pass..1 2...........................1.........17 5......................................................................................................................................................................12 3...................... BACKPROPAGATION ALGORITHM ........................................................................................................................1......................................29 6.....................1.........2 Operation neurons..............................2............................28 6.48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ..... NEURAL NETWORKS................4 Artificial neural networks ............................................................24 5..........................................TABLE CONTENTS LIST FIGURES LIST TABLES 1.................................................................................9 3....................1...................................................................................................................1 Signal preparation ..............1 The basic Artificial Neuron....................................40 8... FUZZY SYSTEMS .................................................43 9.....................................................................................................1 Description the backpropagation algorithm...32 8............ ADAPTIVE NEURO FUZZY INFERENCE SYSTEM.................................................1 Learning algorithm ANFIS .....................51 ............................... THE SIMULATION .................................50 LIST INSERTS .................................................................................1 Real brains..........................40 8.......................................................................................9 3..............43 8.................................... THE REALIZATION THE PROGRAM.................3 Learning ................................................1 Fuzzy Neural Networks .4............................................4 2.........................1 Network parameters ............................. INTRODUCTION .............................6 3...................................................................2 2..........................................................................................................

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