Deterministic Learning Theory for Identification, Recognition, and Control

Nonfiction, Science & Nature, Technology, Electricity, Engineering, Mechanical, Electronics
Cover of the book Deterministic Learning Theory for Identification, Recognition, and Control by Cong Wang, David J. Hill, CRC Press
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Cong Wang, David J. Hill ISBN: 9781351837644
Publisher: CRC Press Publication: October 3, 2018
Imprint: CRC Press Language: English
Author: Cong Wang, David J. Hill
ISBN: 9781351837644
Publisher: CRC Press
Publication: October 3, 2018
Imprint: CRC Press
Language: English

Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way.

A Deterministic View of Learning in Dynamic Environments

The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems.

A New Model of Information Processing

This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Deterministic Learning Theory for Identification, Recognition, and Control presents a unified conceptual framework for knowledge acquisition, representation, and knowledge utilization in uncertain dynamic environments. It provides systematic design approaches for identification, recognition, and control of linear uncertain systems. Unlike many books currently available that focus on statistical principles, this book stresses learning through closed-loop neural control, effective representation and recognition of temporal patterns in a deterministic way.

A Deterministic View of Learning in Dynamic Environments

The authors begin with an introduction to the concepts of deterministic learning theory, followed by a discussion of the persistent excitation property of RBF networks. They describe the elements of deterministic learning, and address dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation of oscillation faults, ECG/EEG pattern recognition, robot learning and control, and security analysis and control of power systems.

A New Model of Information Processing

This book elucidates a learning theory which is developed using concepts and tools from the discipline of systems and control. Fundamental knowledge about system dynamics is obtained from dynamical processes, and is then utilized to achieve rapid recognition of dynamical patterns and pattern-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model of information processing, i.e. a model of dynamical parallel distributed processing (DPDP).

More books from CRC Press

Cover of the book Medical Microbiology Testing in Primary Care by Cong Wang, David J. Hill
Cover of the book Multiple Criteria Decision Making in Supply Chain Management by Cong Wang, David J. Hill
Cover of the book Basics of Precision Engineering by Cong Wang, David J. Hill
Cover of the book Advances in Gear Design and Manufacture by Cong Wang, David J. Hill
Cover of the book Collaborative Construction Information Management by Cong Wang, David J. Hill
Cover of the book What Every Engineer Should Know About Modeling and Simulation by Cong Wang, David J. Hill
Cover of the book Switched Reluctance Motor Drives by Cong Wang, David J. Hill
Cover of the book Trends in Food Safety and Protection by Cong Wang, David J. Hill
Cover of the book Punk Playthings by Cong Wang, David J. Hill
Cover of the book Energy-efficient Office Refurbishment by Cong Wang, David J. Hill
Cover of the book Host-Parasite Interactions by Cong Wang, David J. Hill
Cover of the book The Gamer's Brain by Cong Wang, David J. Hill
Cover of the book The Human Effect in Medicine by Cong Wang, David J. Hill
Cover of the book Turbulence in Open Channel Flows by Cong Wang, David J. Hill
Cover of the book Handbook of Spectroscopy by Cong Wang, David J. Hill
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy