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

................... FUZZY SYSTEMS ..............................................................................2.............................15 4................. THE REALIZATION THE PROGRAM..........................................43 9.........2 Simulation results ....................................................................1...............40 8................................................................1 The basic Artificial Neuron..............................5 2..................................24 5............................................................................................2 Backward pass ....................................9 3............................................2.....1 Fuzzy Neural Networks .......................................................................46 REFERENCES .................40 8...............................................1........................... NEURAL NETWORKS..........1 Network parameters .......2 The ANFIS network..........................1 The 'NNV' network........1 Description the backpropagation algorithm.....................................9 3...2 2.....................28 6..........................................................................................................4 2...............................................1 Real brains....................................26 6................................................14 3..........29 6........40 8...... ADAPTIVE NEURO FUZZY INFERENCE SYSTEM.........................................................................4 Artificial neural networks .................................................................43 8.................1 Division into frames and preprocessing ....................................................................................................................................................................2 Operation neurons.......................................................................................................................................................3 Learning ........................................................50 LIST INSERTS ........................................................................22 5.........................................................1.......4........29 6..................................................... THE SIMULATION .22 5................................12 3..51 ..........................................................5 2............................................................................3 Stop the training ........ THE SPEECH SIGNAL ....................1 Signal preparation ......................17 5.....................................................................................................2 Running the algorithm .......... INTRODUCTION ..43 8.1 Learning algorithm ANFIS ...................................................................................................................................................................................................................1.......................................................................................................................................................................2 Running the simulation ........................TABLE CONTENTS LIST FIGURES LIST TABLES 1...........................................................................................32 8.......................................37 8.........1........................................................................48 LIST SYMBOLS, ABBREVIATIONS AND VARIABLES ......................2 Analysis using filter banks ...................2 2..1.........17 4...........................1 Network parameters .30 7................................................................................................................1 2... CONCLUSION...................................................1 Forward pass...........................................1 The algorithm .........................6 3..................................1........ BACKPROPAGATION ALGORITHM ..........................

---

---