Pramod K. Varshney's Books

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

By: Pramod K. Varshney,Manoj K. Arora

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Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

By: Pramod K. Varshney,Manoj K. Arora

The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.

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Page Count

344

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3662056054

ISBN 13

9783662056059

Secure Networked Inference with Unreliable Data Sources

By: Aditya Vempaty,Bhavya Kailkhura,Pramod K. Varshney

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Secure Networked Inference with Unreliable Data Sources

By: Aditya Vempaty,Bhavya Kailkhura,Pramod K. Varshney

The book presents theory and algorithms for secure networked inference in the presence of Byzantines. It derives fundamental limits of networked inference in the presence of Byzantine data and designs robust strategies to ensure reliable performance for several practical network architectures. In particular, it addresses inference (or learning) processes such as detection, estimation or classification, and parallel, hierarchical, and fully decentralized (peer-to-peer) system architectures. Furthermore, it discusses a number of new directions and heuristics to tackle the problem of design complexity in these practical network architectures for inference.

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Page Count

219

Publisher

Springer

Published Date

ISBN 10

9811323127

ISBN 13

9789811323126

Distributed Detection and Data Fusion

By: Pramod K. Varshney

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Distributed Detection and Data Fusion

By: Pramod K. Varshney

This book provides an introductory treatment of the fundamentals of decision-making in a distributed framework. Classical detection theory assumes that complete observations are available at a central processor for decision-making. More recently, many applications have been identified in which observations are processed in a distributed manner and decisions are made at the distributed processors, or processed data (compressed observations) are conveyed to a fusion center that makes the global decision. Conventional detection theory has been extended so that it can deal with such distributed detection problems. A unified treatment of recent advances in this new branch of statistical decision theory is presented. Distributed detection under different formulations and for a variety of detection network topologies is discussed. This material is not available in any other book and has appeared relatively recently in technical journals. The level of presentation is such that the hook can be used as a graduate-level textbook. Numerous examples are presented throughout the book. It is assumed that the reader has been exposed to detection theory. The book will also serve as a useful reference for practicing engineers and researchers. I have actively pursued research on distributed detection and data fusion over the last decade, which ultimately interested me in writing this book. Many individuals have played a key role in the completion of this book.

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Page Count

286

Publisher

Springer Science & Business Media

Published Date

ISBN 10

1461219043

ISBN 13

9781461219040

Book's by Pramod K. Varshney

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

Secure Networked Inference with Unreliable Data Sources

Secure Networked Inference with Unreliable Data Sources

Distributed Detection and Data Fusion

Distributed Detection and Data Fusion

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