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

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

---

---