Machine Learning For Future Fiber Optic Communication Systems
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Machine Learning for Future Fiber-Optic Communication Systems
Machine Learning for Future Fiber-Optic Communication Systems provides a comprehensive and in-depth treatment of machine learning concepts and techniques applied to key areas within optical communications and networking, reflecting the state-of-the-art research and industrial practices. The book gives knowledge and insights into the role machine learning-based mechanisms will soon play in the future realization of intelligent optical network infrastructures that can manage and monitor themselves, diagnose and resolve problems, and provide intelligent and efficient services to the end users. With up-to-date coverage and extensive treatment of various important topics related to machine learning for fiber-optic communication systems, this book is an invaluable reference for photonics researchers and engineers. It is also a very suitable text for graduate students interested in ML-based signal processing and networking. - Discusses the reasons behind the recent popularity of machine learning (ML) concepts in modern optical communication networks and the why/where/how ML can play a unique role - Presents fundamental ML techniques like artificial neural networks (ANNs), support vector machines (SVMs), K-means clustering, expectation-maximization (EM) algorithm, principal component analysis (PCA), independent component analysis (ICA), reinforcement learning, and more - Covers advanced deep learning (DL) methods such as deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) - - Individual chapters focus on ML applications in key areas of optical communications and networking
Advances in Distributed Computing and Machine Learning
This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by School of Electronics and Engineering, VIT - AP University, Amaravati, Andhra Pradesh, India, during 5–6 January 2024. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.
Green Communication Technologies for Future Networks
This book explores all the energy-efficient communication technologies used for various communication systems and every aspect of these systems, such as green electronics, network protocols, handover, codes, antenna, and the role of artificial intelligence and IoT, including the energy management strategies. It identifies the development of sustainable plans and programs at the communication level within the current legislative framework. Features: Gives a fundamental description of the green communications including granularities of green wired and wireless systems. Describes a comprehensive review of innovations, challenges, and opportunities for green communication. Provides guiding principles on how to build the green communication network. Includes a holistic view of both wireless and wired green communication systems with an emphasis on applications and challenges in each area. Suggests various ways of benchmarking and measuring the performance of green communication systems. This book will be of great interest to graduate students and researchers in green technologies, communications, wireless communication, optical communication, underwater communication, microwave and satellite communication, networking, the internet of things, and energy management.