Digital signal processing (DSP)

Discover up-to-date techniques and algorithms in this concise, intuitive text, with extensive solutions for challenging learning problems.

Get up to speed with the latest developments in Automotive Ethernet technology and implementation with this fully revised third edition.

A practical guide to solving signal integrity problems using s-parameters.

A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.

A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.

Connects fundamental mathematical theory with real-world problems, through efficient and scalable optimization algorithms.

Focuses on practical application of spectral analysis of time series, with examples from environmental, engineering and physical sciences.

A systematic and comprehensive introduction of seismic risk analysis of critical engineering structures, focusing on nuclear power plants.

With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

This user guide presents a popular smoothing tool with practical applications in machine learning, engineering, and statistics.

Discover a new, network-aware coding strategy that uses existing signal interactions to enhance network efficiency, capacity and security.

An intuitive and accessible textbook covering both fundamentals and applications.

Discover a new, network-aware coding strategy that uses existing signal interactions to enhance network efficiency, capacity and security.

A bold retooling of statistics to focus directly on predictive performance with traditional and contemporary data types and methodologies.

An accessible, comprehensive and coherent treatment of MIMO communication, drawing on ideas from information theory and signal processing.

This user guide presents a popular smoothing tool with practical applications in machine learning, engineering, and statistics.

Self-contained presentation of multivariate approximation from classical linear approximation to contemporary nonlinear approximation.

The first unified treatment of the interface between information theory and emerging topics in data science.

A bold retooling of statistics to focus directly on predictive performance with traditional and contemporary data types and methodologies.

Presents an advanced overview of Digital Signal Processing and its applications to exploration seismology, for electrical engineers, geophysicists and petroleum professionals.

An accessible, comprehensive and coherent treatment of MIMO communication, drawing on ideas from information theory and signal processing.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

An innovative and groundbreaking text explaining how wireless AI can determine position, sense motion and vital signs, and identify events and people.

An innovative and groundbreaking text explaining how wireless AI can determine position, sense motion and vital signs, and identify events and people.

This textbook elaborates MIMO wireless communications concepts with emphasis on recent research, techniques and user friendly features.

Learn about the latest theoretical and practical advances in radar signal processing using tools from compressive sensing.

Discover a modern approach to the analysis, modeling and design of high sensitivity phased array systems.

An authoritative text covering the key topics, concepts and analytical tools needed to understand modern communication and radar systems.

Discover a modern approach to the analysis, modeling and design of high sensitivity phased array systems.

An authoritative text covering the key topics, concepts and analytical tools needed to understand modern communication and radar systems.

A modern introduction to the Poisson process, with general point processes and random measures, and applications to stochastic geometry.

An international team of experts covers the pros and cons of different auction formats and lessons learned in the field.

A modern introduction to the Poisson process, with general point processes and random measures, and applications to stochastic geometry.

This is a practical, rigorous guide to the compressive imaging revolution that has fundamentally changed modern image reconstruction.

Develops the theory of Markov and semi-Markov processes in an elementary setting suitable for senior undergraduate and graduate students.

Develops the theory of Markov and semi-Markov processes in an elementary setting suitable for senior undergraduate and graduate students.

A unique, top-down treatment of the principles and practice of signal processing used in real mobile communications systems.

Understand the methods of modern non-stationary signal processing with authoritative insights from a leader in the field.

A unique, top-down treatment of the principles and practice of signal processing used in real mobile communications systems.

Understand the methods of modern non-stationary signal processing with authoritative insights from a leader in the field.

Achieve faster, more efficient heterogeneous network design and optimization with this comprehensive guide.

Achieve faster, more efficient heterogeneous network design and optimization with this comprehensive guide.

Understand design principles of key advanced transmission technologies by means of trade-off analysis using a range of mathematical tools.

Understand design principles of key advanced transmission technologies by means of trade-off analysis using a range of mathematical tools.

This study allows readers to get to grips with the conceptual tools and practical techniques for building robust machine learning in the face of adversaries.

This study allows readers to get to grips with the conceptual tools and practical techniques for building robust machine learning in the face of adversaries.

A comprehensive and mathematically accessible introduction to digital signal processing, covering theory, advanced topics, and applications.

This snapshot of the frontier of statistics and network analysis focuses on the foundational topics of modeling, sampling, and design.