Klasifikace vzorů pomocí fuzzy neuronových sítí

| Kategorie: Diplomové, bakalářské práce  | Tento dokument chci!

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.

Strana 7 z 67

Vámi hledaný text obsahuje tato stránku dokumentu který není autorem určen k veřejnému šíření.

Více info o tomto dokumentu zde!

Jak získat tento dokument?

Poznámky redaktora

.........................................................29 6...............................................................................................................................................37 8....................................................1 Description the backpropagation algorithm..................................1 Network parameters ........1.............................................................................................................................................2 Running the algorithm .......1 Fuzzy Neural Networks . FUZZY SYSTEMS .................................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ..........................................................4...........................2 2...2 Simulation results ..................................................... THE SIMULATION ....................22 5.......15 4....................................................................................................................2..40 8..............................................................................14 3.................................50 LIST INSERTS ......................1..............................17 5.................................................24 5..........................1 Division into frames and preprocessing ..........................................................40 8.....................................................................................28 6........... THE REALIZATION THE PROGRAM..................1 Real brains.................30 7....22 5.............12 3.................................................................................................................................TABLE CONTENTS LIST FIGURES LIST TABLES 1...........................1...........................................................................43 9...................................1..........................1 Forward pass..........................................1 The basic Artificial Neuron........................................................................................................................................................................................................ ADAPTIVE NEURO FUZZY INFERENCE SYSTEM..............................5 2.........32 8.........................6 3..................................................4 Artificial neural networks ..............1...........................................................17 4................................................................... CONCLUSION............29 6.46 REFERENCES .............................1 The 'NNV' network..............43 8............................26 6..1 Network parameters ..........................................2 2....2 Backward pass ..... BACKPROPAGATION ALGORITHM .................................................................................2 The ANFIS network............................2.............1 2................9 3............................................................3 Learning ...................................2 Running the simulation ...........................40 8......................... THE SPEECH SIGNAL .................................................................................................. NEURAL NETWORKS......................................1 The algorithm ..............2 Analysis using filter banks ..................................................................................................................................................................4 2......................1....................................................43 8................5 2..........................................................................................................51 .................................................................................3 Stop the training ..1 Learning algorithm ANFIS ... INTRODUCTION ...1.........1 Signal preparation ......2 Operation neurons.......................................................................................................9 3.....................

---

---