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Neural networks for intelligent signal processing [[electronic resource] /] / Anthony Zaknich
| Neural networks for intelligent signal processing [[electronic resource] /] / Anthony Zaknich |
| Autore | Zaknich Anthony |
| Pubbl/distr/stampa | River Edge, NJ, : World Scientific, c2003 |
| Descrizione fisica | 1 online resource (510 p.) |
| Disciplina | 006.3/2 |
| Collana | Series on innovative intelligence |
| Soggetto topico |
Neural networks (Computer science)
Signal processing - Digital techniques Intelligent control systems |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-94787-3
9786611947873 981-279-685-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Acknowledgments; Foreword; Preface; 1. Introduction; 1.1 Motivation for ANNs; 1.2 ANN Definitions and Main Types; 1.3 Specific ANN Models; 1.4 ANN Black Box Model; 1.5 ANN Implementation; 1.6 When To Use an ANN; 1.7 How To Use an ANN
1.8 General Applications 1.9 Pattern Recognition Examples; 1.9.1 Sheep Eating Phase Identification from Jaw Sounds; 1.9.2 Particle Isolation in SEM Images; 1.9.3 Oxalate Needle Detection in Microscope Images ; 1.10 Function Mapping and Filtering Examples 1.10.1 Water Level from Resonant Sound Analysis 1.10.2 Nonlinear Signal Filtering; 1.11 Motor Control Example; 1.12 ANN Summary; References; 2. A Brief Historical Overview; 2.1 ANN History to 1970; 2.1.1 Key Events prior to 1970; 2.2 ANN History after 1970 2.2.1 Key Events after 1970 to the Mid 1980's 2.2.2 Developments after the Mid 1980's; 2.2.3 Nonparametric Learning From Finite Data; 2.3 Reasons for the Resurgence of Interest in ANNs; 2.4 Historical Summary ; References; 3. Basic Concepts; 3.1 The Basic Model of the Neuron 3.2 Activation Functions 3.3 Topologies; 3.4 Learning; 3.4.1 A Basic Supervised Learning Algorithm; 3.4.2 A Basic Unsupervised Learning Algorithm; 3.5 The Basic McCulloch Pitts and Perceptron Models; 3.6 Vectors Spaces and Matrix Models; 3.6.1 ANN Classifiers 3.6.2 Vectors and Feature Spaces |
| Record Nr. | UNINA-9910454089903321 |
Zaknich Anthony
|
||
| River Edge, NJ, : World Scientific, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Neural networks for intelligent signal processing [[electronic resource] /] / Anthony Zaknich
| Neural networks for intelligent signal processing [[electronic resource] /] / Anthony Zaknich |
| Autore | Zaknich Anthony |
| Pubbl/distr/stampa | River Edge, NJ, : World Scientific, c2003 |
| Descrizione fisica | 1 online resource (510 p.) |
| Disciplina | 006.3/2 |
| Collana | Series on innovative intelligence |
| Soggetto topico |
Neural networks (Computer science)
Signal processing - Digital techniques Intelligent control systems |
| ISBN |
1-281-94787-3
9786611947873 981-279-685-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Acknowledgments; Foreword; Preface; 1. Introduction; 1.1 Motivation for ANNs; 1.2 ANN Definitions and Main Types; 1.3 Specific ANN Models; 1.4 ANN Black Box Model; 1.5 ANN Implementation; 1.6 When To Use an ANN; 1.7 How To Use an ANN
1.8 General Applications 1.9 Pattern Recognition Examples; 1.9.1 Sheep Eating Phase Identification from Jaw Sounds; 1.9.2 Particle Isolation in SEM Images; 1.9.3 Oxalate Needle Detection in Microscope Images ; 1.10 Function Mapping and Filtering Examples 1.10.1 Water Level from Resonant Sound Analysis 1.10.2 Nonlinear Signal Filtering; 1.11 Motor Control Example; 1.12 ANN Summary; References; 2. A Brief Historical Overview; 2.1 ANN History to 1970; 2.1.1 Key Events prior to 1970; 2.2 ANN History after 1970 2.2.1 Key Events after 1970 to the Mid 1980's 2.2.2 Developments after the Mid 1980's; 2.2.3 Nonparametric Learning From Finite Data; 2.3 Reasons for the Resurgence of Interest in ANNs; 2.4 Historical Summary ; References; 3. Basic Concepts; 3.1 The Basic Model of the Neuron 3.2 Activation Functions 3.3 Topologies; 3.4 Learning; 3.4.1 A Basic Supervised Learning Algorithm; 3.4.2 A Basic Unsupervised Learning Algorithm; 3.5 The Basic McCulloch Pitts and Perceptron Models; 3.6 Vectors Spaces and Matrix Models; 3.6.1 ANN Classifiers 3.6.2 Vectors and Feature Spaces |
| Record Nr. | UNINA-9910782282403321 |
|
Zaknich Anthony
|
||
| River Edge, NJ, : World Scientific, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Neural networks for intelligent signal processing / / Anthony Zaknich
| Neural networks for intelligent signal processing / / Anthony Zaknich |
| Autore | Zaknich Anthony |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | River Edge, NJ, : World Scientific, c2003 |
| Descrizione fisica | 1 online resource (510 p.) |
| Disciplina | 006.3/2 |
| Collana | Series on innovative intelligence |
| Soggetto topico |
Neural networks (Computer science)
Signal processing - Digital techniques Intelligent control systems |
| ISBN |
1-281-94787-3
9786611947873 981-279-685-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Acknowledgments; Foreword; Preface; 1. Introduction; 1.1 Motivation for ANNs; 1.2 ANN Definitions and Main Types; 1.3 Specific ANN Models; 1.4 ANN Black Box Model; 1.5 ANN Implementation; 1.6 When To Use an ANN; 1.7 How To Use an ANN
1.8 General Applications 1.9 Pattern Recognition Examples; 1.9.1 Sheep Eating Phase Identification from Jaw Sounds; 1.9.2 Particle Isolation in SEM Images; 1.9.3 Oxalate Needle Detection in Microscope Images ; 1.10 Function Mapping and Filtering Examples 1.10.1 Water Level from Resonant Sound Analysis 1.10.2 Nonlinear Signal Filtering; 1.11 Motor Control Example; 1.12 ANN Summary; References; 2. A Brief Historical Overview; 2.1 ANN History to 1970; 2.1.1 Key Events prior to 1970; 2.2 ANN History after 1970 2.2.1 Key Events after 1970 to the Mid 1980's 2.2.2 Developments after the Mid 1980's; 2.2.3 Nonparametric Learning From Finite Data; 2.3 Reasons for the Resurgence of Interest in ANNs; 2.4 Historical Summary ; References; 3. Basic Concepts; 3.1 The Basic Model of the Neuron 3.2 Activation Functions 3.3 Topologies; 3.4 Learning; 3.4.1 A Basic Supervised Learning Algorithm; 3.4.2 A Basic Unsupervised Learning Algorithm; 3.5 The Basic McCulloch Pitts and Perceptron Models; 3.6 Vectors Spaces and Matrix Models; 3.6.1 ANN Classifiers 3.6.2 Vectors and Feature Spaces |
| Record Nr. | UNINA-9910809089503321 |
|
Zaknich Anthony
|
||
| River Edge, NJ, : World Scientific, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||