Deterministic Learning Theory for Identification, Recognition, and Control: For Identiflcation, Recognition, and Conirol (Automation and Control Engineering)

<p><strong>Deterministic Learning Theory for Identification, Recognition, and Control</strong> 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. </p>  <p><strong>A Deterministic View of Learning in Dynamic Environments</strong></p> <p>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. </p>  <p><strong>A New Model of Information Processing</strong></p> <p>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).</p>

Computers & Technology

Hill, David J.

Wang, Cong

Computer Science

CRC-Press

<p>This book features a collection of papers on the issues, intricacies, and challenges relating to energy and environmental science. It offers expert coverage of the various technological aspects of sustainable energy ecosystems, including processes that improve energy efficiency and reduce CO2 and other greenhouse emissions. It also addresses the need for sustainable technologies in extractive metallurgy, materials processing, and manufacturing industries with energy efficient technologies. Some additional contributions examine renewable energy sources such as solar, wind, and biomass.</p>

Energy Technology 2013: Carbon Dioxide Management and Other Technologies

Science & Math

Pati, Soobhankar

Drelich, Jaroslaw

Jha, Animesh

Neelameggham, Neale R.

Prentice, Leon H.

Technology

<p>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. </p>  <p>A Deterministic View of Learning in Dynamic Environments</p> <p>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. </p>  <p>A New Model of Information Processing</p> <p>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).</p>

Searchable Encryption: From Concepts to Systems (Wireless Networks)

Ren, Kui

Reference

Springer

<p><div> <div> <div>This book comprehensively reviews searchable encryption, which represents a series of research developments that directly enable search functionality over encrypted data. The book majorly covers: 1) the design and implementation of encrypted search algorithms, data structures, and systems that facilitate various forms of search over always-encrypted databases; 2) different threat models, assumptions, and the related security guarantees, when using searchable encryption in the real-world settings; and 3) latest efforts in building full-fledged encrypted database systems that draw insights from searchable encryption constructions.</div> <div><br /></div> <div>The book fits in the timely context, where the necessity of safeguarding important and sensitive data has been globally recognized. Traditional security measures, such as storing data behind network firewalls and layers of access control mechanisms to keep attackers out, are no longer sufficient to cope with the expandinglandscape of surging cyber threats. There is an urgent call to keep sensitive data always encrypted to protect the data at rest, in transit, and in use. Doing so guarantees data confidentiality for owners, even if the data is out of their hands, e.g., hosted at in-the-cloud databases. The daunting challenge is how to perform computation over encrypted data. As we unfold in this book, searchable encryption, as a specific line of research in this broadly defined area, has received tremendous advancements over the past decades.</div> <div><br /></div> This book is majorly oriented toward senior undergraduates, graduate students, and researchers, who want to work in the field and need extensive coverage of encrypted database research. It also targets security practitioners who want to make well-informed deployment choices of the latest advancements in searchable encryption for their targeted applications. Hopefully, this book will be beneficial in both regards.</div> </div> <div><br /></div> <div><br /></div></p>

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