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Machine Learning in Signal Processing Applications Challenges and the Road Ahead

Machine Learning in Signal Processing Applications Challenges and the Road Ahead

Machine Learning in Signal Processing: Applications Challenges and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML as the driving force of the wave of artificial intelligence (AI) provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students post-graduate students research scholars faculties and academicians of computer science and engineering computer science and applications and electronics and telecommunication engineering. | Machine Learning in Signal Processing Applications Challenges and the Road Ahead

GBP 150.00
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Combinatorics of Compositions and Words

Combinatorics of Compositions and Words

A One-Stop Source of Known Results a Bibliography of Papers on the Subject and Novel Research Directions Focusing on a very active area of research in the last decade Combinatorics of Compositions and Words provides an introduction to the methods used in the combinatorics of pattern avoidance and pattern enumeration in compositions and words. It also presents various tools and approaches that are applicable to other areas of enumerative combinatorics. After a historical perspective on research in the area the text introduces techniques to solve recurrence relations including iteration and generating functions. It then focuses on enumeration of basic statistics for compositions. The text goes on to present results on pattern avoidance for subword subsequence and generalized patterns in compositions and then applies these results to words. The authors also cover automata the ECO method generating trees and asymptotic results via random compositions and complex analysis. Highlighting both established and new results this book explores numerous tools for enumerating patterns in compositions and words. It includes a comprehensive bibliography and incorporates the use of the computer algebra systems Maple™ and Mathematica® as well as C++ to perform computations.

GBP 74.99
1

Mobile Crowdsensing

Mobile Crowdsensing

Mobile crowdsensing is a technology that allows large scale cost-effective sensing of the physical world. In mobile crowdsensing mobile personal devices such as smart phones or smart watches come equipped with a variety of sensors that can be leveraged to collect data related to environment transportation healthcare safety and so on. This book presents the first extensive coverage of mobile crowdsensing with examples and insights drawn from the authors’ extensive research on this topic as well as from the research and development of a growing community of researchers and practitioners working in this emerging field. Throughout the text the authors provide the reader with various examples of crowdsensing applications and the building blocks to creating the necessary infrastructure explore the related concepts of mobile sensing and crowdsourcing and examine security and privacy issues introduced by mobile crowdsensing platforms. Provides a comprehensive description of mobile crowdsensing a one-stop shop for all relevant issues pertaining to mobile crowdsensing including motivation applications design and implementation incentive mechanisms and reliability and privacy. Describes the design and implementations of mobile crowdsensing platforms of great interest for the readers working in research and industry to quickly implement and test their systems. Identifies potential issues in building such mobile crowdsensing applications to ensure their usability in real life and presents future directions in mobile crowdsensing by emphasizing the open problems that have to be addressed.

GBP 44.99
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