Rajarshi Mahapatra – författare

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.Provides a detailed theoretical foundation of machine learning and computational intelligence algorithmsHighlights the state of art machine learning-based solutions for communication networksPresents video demonstrations and code snippets on each chapter for easy understanding of the conceptsDiscusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networksDemonstrates applications of machine learning techniques for optical networksThe text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.Provides a detailed theoretical foundation of machine learning and computational intelligence algorithmsHighlights the state of art machine learning-based solutions for communication networksPresents video demonstrations and code snippets on each chapter for easy understanding of the conceptsDiscusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networksDemonstrates applications of machine learning techniques for optical networksThe text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.

The book discusses the foundations of intelligent quantum information processing applied to several real-life engineering problems, including intelligent quantum systems, intelligent quantum communication, intelligent process optimization, and intelligent quantum distributed networks.This book:• Showcases a detailed overview of different quantum machine learning algorithmic frameworks.• Presents real-life case studies and applications.• Provides an in-depth analysis of quantum mechanical principles.• Provides a step-by-step guide in the build-up of quantum inspired/quantum intelligent information processing systems.• Provides a video demonstration on each chapter for better understanding.It will serve as an ideal reference text for graduate students and academic researchers in fields such as electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The book discusses the foundations of intelligent quantum information processing applied to several real-life engineering problems, including intelligent quantum systems, intelligent quantum communication, intelligent process optimization, and intelligent quantum distributed networks.This book:• Showcases a detailed overview of different quantum machine learning algorithmic frameworks.• Presents real-life case studies and applications.• Provides an in-depth analysis of quantum mechanical principles.• Provides a step-by-step guide in the build-up of quantum inspired/quantum intelligent information processing systems.• Provides a video demonstration on each chapter for better understanding.It will serve as an ideal reference text for graduate students and academic researchers in fields such as electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The book discusses the foundations of intelligent quantum information processing applied to several real-life engineering problems, including intelligent quantum systems, intelligent quantum communication, intelligent process optimization, and intelligent quantum distributed networks.This book:* Showcases a detailed overview of different quantum machine learning algorithmic frameworks.* Presents real-life case studies and applications.* Provides an in-depth analysis of quantum mechanical principles.* Provides a step-by-step guide in the build-up of quantum inspired/quantum intelligent information processing systems.* Provides a video demonstration on each chapter for better understanding.It will serve as an ideal reference text for graduate students and academic researchers in fields such as electrical engineering, electronics and communication engineering, computer engineering, and information technology.

The book discusses the foundations of intelligent quantum information processing applied to several real-life engineering problems, including intelligent quantum systems, intelligent quantum communication, intelligent process optimization, and intelligent quantum distributed networks.This book:* Showcases a detailed overview of different quantum machine learning algorithmic frameworks.* Presents real-life case studies and applications.* Provides an in-depth analysis of quantum mechanical principles.* Provides a step-by-step guide in the build-up of quantum inspired/quantum intelligent information processing systems.* Provides a video demonstration on each chapter for better understanding.It will serve as an ideal reference text for graduate students and academic researchers in fields such as electrical engineering, electronics and communication engineering, computer engineering, and information technology.

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.

Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms Highlights the state of art machine learning-based solutions for communication networks Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks Demonstrates applications of machine learning techniques for optical networks

The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.

Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms Highlights the state of art machine learning-based solutions for communication networks Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks Demonstrates applications of machine learning techniques for optical networks

The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.