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Biblioteca

MARC Lista (tabellare)
Complex-valued neural networks : advances and applications / / edited by Akira Hirose
Complex-valued neural networks : advances and applications / / edited by Akira Hirose
Pubbl/distr/stampa Hoboken [New Jersey] : , : Wiley, , 2013
Descrizione fisica 1 online resource (310 p.)
Disciplina 006.3/2
006.32
Altri autori (Persone) HiroseAkira <1963->
Collana IEEE Press Series on Computational Intelligence
Soggetto topico Neural networks (Computer science)
Neural networks (Computer science) - Industrial applications
ISBN 1-118-59006-6
1-118-59014-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface xv -- 1 Application Fields and Fundamental Merits 1 -- Akira Hirose -- 1.1 Introduction 1 -- 1.2 Applications of Complex-Valued Neural Networks 2 -- 1.3 What is a complex number? 5 -- 1.4 Complex numbers in feedforward neural networks 8 -- 1.5 Metric in complex domain 12 -- 1.6 Experiments to elucidate the generalization characteristics 16 -- 1.7 Conclusions 26 -- 2 Neural System Learning on Complex-Valued Manifolds 33 -- Simone Fiori -- 2.1 Introduction 34 -- 2.2 Learning Averages over the Lie Group of Unitary Matrices 35 -- 2.3 Riemannian-Gradient-Based Learning on the Complex Matrix-Hypersphere 41 -- 2.4 Complex ICA Applied to Telecommunications 49 -- 2.5 Conclusion 53 -- 3 N-Dimensional Vector Neuron and Its Application to the N-Bit Parity Problem 59 -- Tohru Nitta -- 3.1 Introduction 59 -- 3.2 Neuron Models with High-Dimensional Parameters 60 -- 3.3 N-Dimensional Vector Neuron 65 -- 3.4 Discussion 69 -- 3.5 Conclusion 70 -- 4 Learning Algorithms in Complex-Valued Neural Networks using Wirtinger Calculus 75 -- Md. Faijul Amin and Kazuyuki Murase -- 4.1 Introduction 76 -- 4.2 Derivatives in Wirtinger Calculus 78 -- 4.3 Complex Gradient 80 -- 4.4 Learning Algorithms for Feedforward CVNNs 82 -- 4.5 Learning Algorithms for Recurrent CVNNs 91 -- 4.6 Conclusion 99 -- 5 Quaternionic Neural Networks for Associative Memories 103 -- Teijiro Isokawa, Haruhiko Nishimura, and Nobuyuki Matsui -- 5.1 Introduction 104 -- 5.2 Quaternionic Algebra 105 -- 5.3 Stability of Quaternionic Neural Networks 108 -- 5.4 Learning Schemes for Embedding Patterns 124 -- 5.5 Conclusion 128 -- 6 Models of Recurrent Clifford Neural Networks and Their Dynamics 133 -- Yasuaki Kuroe -- 6.1 Introduction 134 -- 6.2 Clifford Algebra 134 -- 6.3 Hopfield-Type Neural Networks and Their Energy Functions 137 -- 6.4 Models of Hopfield-Type Clifford Neural Networks 139 -- 6.5 Definition of Energy Functions 140 -- 6.6 Existence Conditions of Energy Functions 142 -- 6.7 Conclusion 149 -- 7 Meta-cognitive Complex-valued Relaxation Network and its Sequential Learning Algorithm 153 -- Ramasamy Savitha, Sundaram Suresh, and Narasimhan Sundararajan.
7.1 Meta-cognition in Machine Learning 154 -- 7.2 Meta-cognition in Complex-valued Neural Networks 156 -- 7.3 Meta-cognitive Fully Complex-valued Relaxation Network 164 -- 7.4 Performance Evaluation of McFCRN: Synthetic Complexvalued Function Approximation Problem 171 -- 7.5 Performance Evaluation of McFCRN: Real-valued Classification Problems 172 -- 7.6 Conclusion 178 -- 8 Multilayer Feedforward Neural Network with Multi-Valued Neurons for Brain-Computer Interfacing 185 -- Nikolay V. Manyakov, Igor Aizenberg, Nikolay Chumerin, and Marc M. Van Hulle -- 8.1 Brain-Computer Interface (BCI) 185 -- 8.2 BCI Based on Steady-State Visual Evoked Potentials 188 -- 8.3 EEG Signal Preprocessing 192 -- 8.4 Decoding Based on MLMVN for Phase-Coded SSVEP BCI 196 -- 8.5 System Validation 201 -- 8.6 Discussion 203 -- 9 Complex-Valued B-Spline Neural Networks for Modeling and Inverse of Wiener Systems 209 -- Xia Hong, Sheng Chen and Chris J. Harris -- 9.1 Introduction 210 -- 9.2 Identification and Inverse of Complex-Valued Wiener Systems 211 -- 9.3 Application to Digital Predistorter Design 222 -- 9.4 Conclusions 229 -- 10 Quaternionic Fuzzy Neural Network for View-invariant Color Face Image Recognition 235 -- Wai Kit Wong, Gin Chong Lee, Chu Kiong Loo, Way Soong Lim, and Raymond Lock -- 10.1 Introduction 236 -- 10.2 Face Recognition System 238 -- 10.3 Quaternion-Based View-invariant Color Face Image Recognition 244 -- 10.4 Enrollment Stage and Recognition Stage for Quaternion- Based Color Face Image Correlator 255 -- 10.5 Max-Product Fuzzy Neural Network Classifier 260 -- 10.6 Experimental Results 266 -- 10.7 Conclusion and Future Research Directions 274 -- References 274 -- Index 279.
Record Nr. UNINA-9910141604503321
Hoboken [New Jersey] : , : Wiley, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Complex-valued neural networks : advances and applications / / edited by Akira Hirose
Complex-valued neural networks : advances and applications / / edited by Akira Hirose
Pubbl/distr/stampa Hoboken [New Jersey] : , : Wiley, , 2013
Descrizione fisica 1 online resource (310 p.)
Disciplina 006.3/2
006.32
Altri autori (Persone) HiroseAkira <1963->
Collana IEEE Press Series on Computational Intelligence
Soggetto topico Neural networks (Computer science)
Neural networks (Computer science) - Industrial applications
ISBN 1-118-59006-6
1-118-59014-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface xv -- 1 Application Fields and Fundamental Merits 1 -- Akira Hirose -- 1.1 Introduction 1 -- 1.2 Applications of Complex-Valued Neural Networks 2 -- 1.3 What is a complex number? 5 -- 1.4 Complex numbers in feedforward neural networks 8 -- 1.5 Metric in complex domain 12 -- 1.6 Experiments to elucidate the generalization characteristics 16 -- 1.7 Conclusions 26 -- 2 Neural System Learning on Complex-Valued Manifolds 33 -- Simone Fiori -- 2.1 Introduction 34 -- 2.2 Learning Averages over the Lie Group of Unitary Matrices 35 -- 2.3 Riemannian-Gradient-Based Learning on the Complex Matrix-Hypersphere 41 -- 2.4 Complex ICA Applied to Telecommunications 49 -- 2.5 Conclusion 53 -- 3 N-Dimensional Vector Neuron and Its Application to the N-Bit Parity Problem 59 -- Tohru Nitta -- 3.1 Introduction 59 -- 3.2 Neuron Models with High-Dimensional Parameters 60 -- 3.3 N-Dimensional Vector Neuron 65 -- 3.4 Discussion 69 -- 3.5 Conclusion 70 -- 4 Learning Algorithms in Complex-Valued Neural Networks using Wirtinger Calculus 75 -- Md. Faijul Amin and Kazuyuki Murase -- 4.1 Introduction 76 -- 4.2 Derivatives in Wirtinger Calculus 78 -- 4.3 Complex Gradient 80 -- 4.4 Learning Algorithms for Feedforward CVNNs 82 -- 4.5 Learning Algorithms for Recurrent CVNNs 91 -- 4.6 Conclusion 99 -- 5 Quaternionic Neural Networks for Associative Memories 103 -- Teijiro Isokawa, Haruhiko Nishimura, and Nobuyuki Matsui -- 5.1 Introduction 104 -- 5.2 Quaternionic Algebra 105 -- 5.3 Stability of Quaternionic Neural Networks 108 -- 5.4 Learning Schemes for Embedding Patterns 124 -- 5.5 Conclusion 128 -- 6 Models of Recurrent Clifford Neural Networks and Their Dynamics 133 -- Yasuaki Kuroe -- 6.1 Introduction 134 -- 6.2 Clifford Algebra 134 -- 6.3 Hopfield-Type Neural Networks and Their Energy Functions 137 -- 6.4 Models of Hopfield-Type Clifford Neural Networks 139 -- 6.5 Definition of Energy Functions 140 -- 6.6 Existence Conditions of Energy Functions 142 -- 6.7 Conclusion 149 -- 7 Meta-cognitive Complex-valued Relaxation Network and its Sequential Learning Algorithm 153 -- Ramasamy Savitha, Sundaram Suresh, and Narasimhan Sundararajan.
7.1 Meta-cognition in Machine Learning 154 -- 7.2 Meta-cognition in Complex-valued Neural Networks 156 -- 7.3 Meta-cognitive Fully Complex-valued Relaxation Network 164 -- 7.4 Performance Evaluation of McFCRN: Synthetic Complexvalued Function Approximation Problem 171 -- 7.5 Performance Evaluation of McFCRN: Real-valued Classification Problems 172 -- 7.6 Conclusion 178 -- 8 Multilayer Feedforward Neural Network with Multi-Valued Neurons for Brain-Computer Interfacing 185 -- Nikolay V. Manyakov, Igor Aizenberg, Nikolay Chumerin, and Marc M. Van Hulle -- 8.1 Brain-Computer Interface (BCI) 185 -- 8.2 BCI Based on Steady-State Visual Evoked Potentials 188 -- 8.3 EEG Signal Preprocessing 192 -- 8.4 Decoding Based on MLMVN for Phase-Coded SSVEP BCI 196 -- 8.5 System Validation 201 -- 8.6 Discussion 203 -- 9 Complex-Valued B-Spline Neural Networks for Modeling and Inverse of Wiener Systems 209 -- Xia Hong, Sheng Chen and Chris J. Harris -- 9.1 Introduction 210 -- 9.2 Identification and Inverse of Complex-Valued Wiener Systems 211 -- 9.3 Application to Digital Predistorter Design 222 -- 9.4 Conclusions 229 -- 10 Quaternionic Fuzzy Neural Network for View-invariant Color Face Image Recognition 235 -- Wai Kit Wong, Gin Chong Lee, Chu Kiong Loo, Way Soong Lim, and Raymond Lock -- 10.1 Introduction 236 -- 10.2 Face Recognition System 238 -- 10.3 Quaternion-Based View-invariant Color Face Image Recognition 244 -- 10.4 Enrollment Stage and Recognition Stage for Quaternion- Based Color Face Image Correlator 255 -- 10.5 Max-Product Fuzzy Neural Network Classifier 260 -- 10.6 Experimental Results 266 -- 10.7 Conclusion and Future Research Directions 274 -- References 274 -- Index 279.
Record Nr. UNINA-9910830306903321
Hoboken [New Jersey] : , : Wiley, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui