Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes.
Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Polynomial Signal Processing
Despite our growing understanding of the properties and capabilities of nonlinear filters, there persists the belief among engineers that these filters are too complex to implement. This book debunks the myth that all nonlinear filters are complex with its coverage of the polynomial filter. It examines all major aspects of the technology, including system modeling, speed analysis, image processing, communications, biological signal processing, semiconductor modeling, neutral sets, and more.
Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes.
Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Polynomial Signal Processing
Despite our growing understanding of the properties and capabilities of nonlinear filters, there persists the belief among engineers that these filters are too complex to implement. This book debunks the myth that all nonlinear filters are complex with its coverage of the polynomial filter. It examines all major aspects of the technology, including system modeling, speed analysis, image processing, communications, biological signal processing, semiconductor modeling, neutral sets, and more.