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299 results in Communications and signal processing

Page 1 of 15

Coding for Erasure Channels
  • Marco Chiani, Gianluigi Liva, Enrico Paolini, Balázs Matuz
  • Coming soon
  • Expected online publication date:
    January 2026
    Print publication:
    31 January 2026
  • Understand how to make wireless communication networks, digital storage systems and computer networks robust and reliable in the first unified, comprehensive treatment of erasure correcting codes. Data loss is unavoidable in modern computer networks; as such, data recovery can be crucial and these codes can play a central role. Through a focused, detailed approach, you will gain a solid understanding of the theory and the practical knowledge to analyze, design and implement erasure codes for future computer networks and digital storage systems. Starting with essential concepts from algebra and classical coding theory, the book provides specific code descriptions and efficient design methods, with practical applications and advanced techniques stemming from cutting-edge research. This is an accessible and self-contained reference, invaluable to both theorists and practitioners in electrical engineering, computer science and mathematics.

Classical and Quantum Information Theory
  • Uncertainty, Information, and Correlation
  • Osvaldo Simeone
  • Coming soon
  • Expected online publication date:
    December 2025
    Print publication:
    31 December 2025
  • Discover the foundations of classical and quantum information theory in the digital age with this modern introductory textbook. Familiarise yourself with core topics such as uncertainty, correlation, and entanglement before exploring modern techniques and concepts including tensor networks, quantum circuits and quantum discord. Deepen your understanding and extend your skills with over 250 thought-provoking end-of-chapter problems, with solutions for instructors, and explore curated further reading. Understand how abstract concepts connect to real-world scenarios with over 400 examples, including numerical and conceptual illustrations, and emphasising practical applications. Build confidence as chapters progressively increase in complexity, alternating between classic and quantum systems. This is the ideal textbook for senior undergraduate and graduate students in electrical engineering, computer science, and applied mathematics, looking to master the essentials of contemporary information theory.

Linear Cryptanalysis
  • Tim Beyne, Vincent Rijmen
  • Coming soon
  • Expected online publication date:
    November 2025
    Print publication:
    30 November 2025
  • Applications of cryptography are plenty in everyday life. This guidebook is about the security analysis or 'cryptanalysis' of the basic building blocks on which these applications rely. Rather than covering a variety of techniques at an introductory level, this book provides a comprehensive and in-depth treatment of linear cryptanalysis. The subject is introduced from a mathematical point of view, providing an overview of the most influential papers on linear cryptanalysis and placing them in a consistent framework based on linear algebra. A large number of examples and exercises are included, drawing upon practice as well as theory. The book is accessible to students with no prior knowledge of cryptography. It covers linear cryptanalysis starting from the basics, including linear approximations and trails, correlation matrices, automatic search, key-recovery techniques, up to advanced topics, such as multiple and multidimensional linear cryptanalysis, zero-correlation approximations, and the geometric approach.

Introduction to Machine Learning
  • From Math to Code
  • Ruye Wang
  • Coming soon
  • Expected online publication date:
    September 2025
    Print publication:
    30 September 2025
  • Emphasizing how and why machine learning algorithms work, this introductory textbook bridges the gap between the theoretical foundations of machine learning and its practical algorithmic and code-level implementation. Over 85 thorough worked examples, in both Matlab and Python, demonstrate how algorithms are implemented and applied whilst illustrating the end result. Over 75 end-of-chapter problems empower students to develop their own code to implement these algorithms, equipping them with hands-on experience. Matlab coding examples demonstrate how a mathematical idea is converted from equations to code, and provide a jumping off point for students, supported by in-depth coverage of essential mathematics including multivariable calculus, linear algebra, probability and statistics, numerical methods, and optimization. Accompanied online by instructor lecture slides, downloadable Python code and additional appendices, this is an excellent introduction to machine learning for senior undergraduate and graduate students in Engineering and Computer Science.

Wireless Communications and Machine Learning
  • Le Liang, Shi Jin, Hao Ye, Geoffrey Ye Li
  • Coming soon
  • Expected online publication date:
    September 2025
    Print publication:
    03 July 2025
  • This focused textbook demonstrates cutting-edge concepts at the intersection of machine learning (ML) and wireless communications, providing students with a deep and insightful understanding of this emerging field. It introduces students to a broad array of ML tools for effective wireless system design, and supports them in exploring ways in which future wireless networks can be designed to enable more effective deployment of federated and distributed learning techniques to enable AI systems. Requiring no previous knowledge of ML, this accessible introduction includes over 20 worked examples demonstrating the use of theoretical principles to address real-world challenges, and over 100 end-of-chapter exercises to cement student understanding, including hands-on computational exercises using Python. Accompanied by code supplements and solutions for instructors, this is the ideal textbook for a single-semester senior undergraduate or graduate course for students in electrical engineering, and an invaluable reference for academic researchers and professional engineers in wireless communications.

Financial Data Science
  • Giuseppe Calafiore, Laurent El Ghaoui, Giulia Fracastoro, Alicia Tsai
  • Coming soon
  • Expected online publication date:
    August 2025
    Print publication:
    17 July 2025
  • Confidently analyze, interpret and act on financial data with this practical introduction to the fundamentals of financial data science. Master the fundamentals with step-by-step introductions to core topics will equip you with a solid foundation for applying data science techniques to real-world complex financial problems. Extract meaningful insights as you learn how to use data to lead informed, data-driven decisions, with over 50 examples and case studies and hands-on Matlab and Python code. Explore cutting-edge techniques and tools in machine learning for financial data analysis, including deep learning and natural language processing. Accessible to readers without a specialized background in finance or machine learning, and including coverage of data representation and visualization, data models and estimation, principal component analysis, clustering methods, optimization tools, mean/variance portfolio optimization and financial networks, this is the ideal introduction for financial services professionals, and graduate students in finance and data science.

Wireless Communication
  • Theory and Applications
  • Mainak Chowdhury, Arumita Biswas
  • Coming soon
  • Expected online publication date:
    June 2025
    Print publication:
    16 January 2017
  • Owing to the rapid developments and growth in the telecommunications industry, the need to develop relevant skills in this field are in high demand. Wireless technology helps to exchange the information between portable devices situated globally. In order to fulfil the demands of this developing field, a unified approach between fundamental concepts and advanced topics is required. The book bridges the gap with a focus on key concepts along with the latest developments including turbo coding, smart antennas, multiple input multiple output (MIMO) system, and software defined radio. It also underpins the design requirements of wireless systems and provides comprehensive coverage of the cellular system and its generations: 3G and 4G (Long Term Evolution). With numerous solved examples, numerical questions, open book exam questions, and illustrations, undergraduates and graduate students will find this to be a readable and highly useful text.

Modern Signal Processing
  • Edited by Daniel N. Rockmore, Dennis M. Healy, Jr
  • Mathematical Sciences Research Institute
  • Published online:
    25 June 2025
    Print publication:
    05 April 2004
  • Signal processing is everywhere in modern technology. Its mathematical basis and many areas of application are the subject of this book, based on a series of graduate-level lectures held at the Mathematical Sciences Research Institute. Emphasis is on challenges in the subject, particular techniques adapted to particular technologies, and certain advances in algorithms and theory. The book covers two main areas: computational harmonic analysis, envisioned as a technology for efficiently analysing real data using inherent symmetries; and the challenges inherent in the acquisition, processing and analysis of images and sensing data in general [EMDASH] ranging from sonar on a submarine to a neuroscientist's fMRI study.

Inverse Problems and Applications
  • Inside Out II
  • Edited by Gunther Uhlmann
  • Mathematical Sciences Research Institute
  • Published online:
    30 May 2025
    Print publication:
    17 December 2012
  • Inverse problems lie at the heart of contemporary scientific inquiry and technological development. Applications include a variety of medical and other imaging techniques, which are used for early detection of cancer and pulmonary edema, location of oil and mineral deposits in the Earth's interior, creation of astrophysical images from telescope data, finding cracks and interfaces within materials, shape optimization, model identification in growth processes, and modeling in the life sciences among others. The expository survey essays in this book describe recent developments in inverse problems and imaging, including hybrid or couple-physics methods arising in medical imaging, Calderon's problem and electrical impedance tomography, inverse problems arising in global seismology and oil exploration, inverse spectral problems, and the study of asymptotically hyperbolic spaces. It is suitable for graduate students and researchers interested in inverse problems and their applications.

Partially Observed Markov Decision Processes
  • Filtering, Learning and Controlled Sensing
  • 2nd edition
  • Vikram Krishnamurthy
  • Published online:
    16 May 2025
    Print publication:
    05 June 2025
  • Covering formulation, algorithms and structural results and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering, operations research, and economics to understand the underlying unifying themes without getting weighed down by mathematical technicalities. In light of major advances in machine learning over the past decade, this edition includes a new Part V on inverse reinforcement learning as well as a new chapter on non-parametric Bayesian inference (for Dirichlet processes and Gaussian processes), variational Bayes and conformal prediction.

Theory of Image Formation
  • 2nd edition
  • Richard E. Blahut
  • Published online:
    17 April 2025
    Print publication:
    24 April 2025
  • Fully revised and updated, the second edition of this classic text is the definitive guide to the mathematical models underlying imaging from sensed data. Building on fundamental principles derived from the two- and three-dimensional Fourier transform, and other key mathematical concepts, it introduces a broad range of imaging modalities within a unified framework, emphasising universal theoretical concepts over specific physical aspects. This expanded edition presents new coverage of optical-coherence microscopy, electron-beam microscopy, near-field microscopy, and medical imaging modalities including MRI, CAT, ultrasound, and the imaging of viruses, and introduces additional end-of-chapter problems to support reader understanding. Encapsulating the author's fifty years of experience in the field, this is the ideal introduction for senior undergraduate and graduate students, academic researchers, and professional engineers across engineering and the physical sciences.

Fundamentals of Digital Communication Systems
  • Tolga M. Duman
  • Published online:
    10 March 2025
    Print publication:
    23 January 2025
  • This dynamic textbook provides students with a concise and accessible introduction to the fundamentals of modern digital communications systems. Building from first principles, its comprehensive approach equips students with all of the mathematical tools, theoretical knowledge, and practical understanding they need to excel. It equips students with a strong mathematical foundation spanning signals and systems, probability, random variables, and random processes, and introduces students to key concepts in digital information sources, analog-to-digital conversion, digital modulation, power spectra, multi-carrier modulation, and channel coding. It includes over 85 illustrative examples, and more than 270 theoretical and computational end-of-chapter problems, allowing students to connect theory to practice, and is accompanied by downloadable Matlab code, and a digital solutions manual for instructors. Suitable for a single-semester course, this succinct textbook is an ideal introduction to the field of digital communications for senior undergraduate students in electrical engineering.

Channel Codes
  • Classical and Modern
  • 2nd edition
  • William E. Ryan, Shu Lin, Stephen G. Wilson
  • Published online:
    06 March 2025
    Print publication:
    21 November 2024
  • Channel coding lies at the heart of digital communication and data storage. Fully updated, including a new chapter on polar codes, this detailed introduction describes the core theory of channel coding, decoding algorithms, implementation details, and performance analyses. This new edition includes over 50 new end-of-chapter problems and new figures and worked examples throughout. The authors emphasize the practical approach and present clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes, detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, product codes as well as polar codes for error correction and detection, providing a one-stop resource for classical and modern coding techniques. Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then extend to advanced topics such as code ensemble performance analyses and algebraic code design.

Machine Learning with Python
  • Principles and Practical Techniques
  • Parteek Bhatia
  • Published online:
    22 February 2025
    Print publication:
    31 July 2025
  • Machine learning has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence. This lucid textbook presents the theoretical foundations of machine learning algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a 'learning by doing' approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner.

Information Theory
  • From Coding to Learning
  • Yury Polyanskiy, Yihong Wu
  • Published online:
    09 January 2025
    Print publication:
    02 January 2025
  • This enthusiastic introduction to the fundamentals of information theory builds from classical Shannon theory through to modern applications in statistical learning, equipping students with a uniquely well-rounded and rigorous foundation for further study. Introduces core topics such as data compression, channel coding, and rate-distortion theory using a unique finite block-length approach. With over 210 end-of-part exercises and numerous examples, students are introduced to contemporary applications in statistics, machine learning and modern communication theory. This textbook presents information-theoretic methods with applications in statistical learning and computer science, such as f-divergences, PAC Bayes and variational principle, Kolmogorov's metric entropy, strong data processing inequalities, and entropic upper bounds for statistical estimation. Accompanied by a solutions manual for instructors, and additional standalone chapters on more specialized topics in information theory, this is the ideal introductory textbook for senior undergraduate and graduate students in electrical engineering, statistics, and computer science.

Molecular Communication
  • 2nd edition
  • Tadashi Nakano, Andrew Eckford, Tokuko Haraguchi
  • Published online:
    12 December 2024
    Print publication:
    19 December 2024
  • Fully revised and updated, this second edition is a comprehensive introduction to molecular communication including the theory, applications, and latest developments. Written with accessibility in mind, it requires little background knowledge, and carefully introduces the relevant aspects of biology and information theory, as well as practical systems. Capturing the significant changes and developments in the past decade, this edition includes seven new chapters covering: the architecture of molecular communication; modelling of biological molecular communication; mobile molecular communication; macroscale systems; design of components and bio-nanomachine formations. The authors present the biological foundations followed by analyses of biological systems in terms of communication theory, and go on to discuss the practical aspects of designing molecular communication systems such as drug delivery, lab-on-a-chip, and tissue engineering. Including case studies and experimental techniques, this remains a definitive guide to molecular communication for graduate students and researchers in electrical engineering, computer science, and molecular biology.

Digital Communications
  • A Foundational Approach
  • Robert F. H. Fischer, Johannes B. Huber
  • Published online:
    22 November 2024
    Print publication:
    31 October 2024
  • Introducing the fundamentals of digital communication with a robust bottom-up approach, this textbook is designed to equip senior undergraduate and graduate students in communications engineering with the core skills they need to assess, compare, and design state-of-the-art digital communication systems. Delivering a fast, concise grounding in key algorithms, concepts, and mathematical principles, this textbook provides all the mathematical tools for understanding state-of-the-art digital communications. The authors prioritise readability and accessibility, to quickly get students up to speed on key topics in digital communication, and includes all relevant derivations. Presenting over 70 carefully designed multi-part end-of-chapter problems with over 360 individual questions, this textbook gauges student understanding and translates knowledge to real-world problem solving. Accompanied online by interactive visualizations of signals, downloadable Matlab code, and solutions for instructors.

Linear Algebra for Data Science, Machine Learning, and Signal Processing
  • Jeffrey A. Fessler, Raj Rao Nadakuditi
  • Published online:
    01 November 2024
    Print publication:
    16 May 2024
  • Maximise student engagement and understanding of matrix methods in data-driven applications with this modern teaching package. Students are introduced to matrices in two preliminary chapters, before progressing to advanced topics such as the nuclear norm, proximal operators and convex optimization. Highlighted applications include low-rank approximation, matrix completion, subspace learning, logistic regression for binary classification, robust PCA, dimensionality reduction and Procrustes problems. Extensively classroom-tested, the book includes over 200 multiple-choice questions suitable for in-class interactive learning or quizzes, as well as homework exercises (with solutions available for instructors). It encourages active learning with engaging 'explore' questions, with answers at the back of each chapter, and Julia code examples to demonstrate how the mathematics is actually used in practice. A suite of computational notebooks offers a hands-on learning experience for students. This is a perfect textbook for upper-level undergraduates and first-year graduate students who have taken a prior course in linear algebra basics.

Time-Variant and Quasi-separable Systems
  • Matrix Theory, Recursions and Computations
  • Patrick Dewilde, Klaus Diepold, Alle-Jan Van der Veen
  • Published online:
    24 October 2024
    Print publication:
    31 October 2024
  • Matrix theory is the lingua franca of everyone who deals with dynamically evolving systems, and familiarity with efficient matrix computations is an essential part of the modern curriculum in dynamical systems and associated computation. This is a master's-level textbook on dynamical systems and computational matrix algebra. It is based on the remarkable identity of these two disciplines in the context of linear, time-variant, discrete-time systems and their algebraic equivalent, quasi-separable systems. The authors' approach provides a single, transparent framework that yields simple derivations of basic notions, as well as new and fundamental results such as constrained model reduction, matrix interpolation theory and scattering theory. This book outlines all the fundamental concepts that allow readers to develop the resulting recursive computational schemes needed to solve practical problems. An ideal treatment for graduate students and academics in electrical and computer engineering, computer science and applied mathematics.

Signals, Systems, and Signal Processing
  • P. P. Vaidyanathan
  • Published online:
    29 August 2024
    Print publication:
    13 June 2024
  • This innovative introduction to the foundations of signals, systems, and transforms emphasises discrete-time concepts, smoothing the transition towards more advanced study in Digital Signal Processing (DSP). A digital-first approach, introducing discrete-time concepts from the beginning, equips students with a firm theoretical foundation in signals and systems, while emphasising topics fundamental to understanding DSP. Continuous-time approaches are introduced in later chapters, providing students with a well-rounded understanding that maintains a strong digital emphasis. Real-world applications, including music signals, signal denoising systems, and digital communication systems, are introduced to encourage student motivation. Early introduction of core concepts in digital filtering, DFT and FFT provide a frictionless transition through to more advanced study. Over 325 end-of-chapter problems, and over 50 computational problems using Matlab. Accompanied online by solutions and code for instructors, this rigorous textbook is ideal for undergraduate students in electrical engineering studying an introductory course in signals, systems, and signal processing.

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