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Cognitive Electronic Warfare: An Artificial Intelligence Approach
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Cognitive Electronic Warfare: An Artificial Intelligence Approach

Unabridged

Book Details

Format Hardback or Cased Book
ISBN-10 1630818119
ISBN-13 9781630818111
Edition Unabridged
Publisher Artech House Publishers
Imprint Artech House Publishers
Country of Manufacture GB
Country of Publication GB
Publication Date Jul 31st, 2021
Print length 288 Pages
Weight 516 grams
Dimensions 15.80 x 23.60 x 2.40 cms
Product Classification: Electronic devices & materialsRadar
Ksh 16,900.00
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This book is an overview of how cognitive systems and artificial intelligence

(AI) can be used in electronic warfare (EW). Readers will learn how EW

systems respond more quickly and effectively to battlefield conditions

where sophisticated RF transmitters and spectrum congestion put a high

priority on EW systems that can characterize and classify novel waveforms,

discern intent, and devise and test countermeasures. Specific techniques

are covered for optimizing a cognitive EW system as well as evaluating

its ability to learn new information in real time.

This comprehensive book gives an overview of how cognitive systems and artificial intelligence (AI) can be used in electronic warfare (EW). Readers will learn how EW systems respond more quickly and effectively to battlefield conditions where sophisticated radars and spectrum congestion put a high priority on EW systems that can characterize and classify novel waveforms, discern intent, and devise and test countermeasures. Specific techniques are covered for optimizing a cognitive EW system as well as evaluating its ability to learn new information in real time. The book presents AI for electronic support (ES), including characterization, classification, patterns of life, and intent recognition. Optimization techniques, including temporal tradeoffs and distributed optimization challenges are also discussed. The issues concerning real-time in-mission machine learning and suggests some approaches to address this important challenge are presented and described. The book covers electronic battle management, data management, and knowledge sharing. Evaluation approaches, including how to show that a machine learning system can learn how to handle novel environments, are also discussed. Written by experts with first-hand experience in AI-based EW, this is the first book on in-mission real-time learning and optimization.

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