Understanding Digital Signal Processing
Amazon.com’s Top-Selling DSP Book for Seven Straight Years—Now Fully Updated!
Understanding Digital Signal Processing, Third Edition, is quite simply the best resource for engineers and other technical professionals who want to master and apply today’s latest DSP techniques. Richard G. Lyons has updated and expanded his best-selling second edition to reflect the newest technologies, building on the exceptionally readable coverage that made it the favorite of DSP professionals...
The Scientist & Engineer's Guide to Digital Signal Processing
Clear and concise explanations of practical DSP techniques. Written for scientists and engineers needing the power of DSP, but not the abstract theory and detailed mathematics.
Think DSP: Digital Signal Processing in Python
Think DSP: Digital Signal Processing in Python is an introduction to signal processing and system analysis using a computational approach. The premise of this book (like the others in the Think X series) is that if you know how to program, you can use that skill to learn other things. By the end of the first chapter, you'll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Subsequent chapters follow a logical progression that develops the...
The Essential Guide to Digital Signal Processing (Essential Guide Series)
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- How signal processing works: clear, simple explanations in plain English
- Breakthrough DSP applications: from smartphones to healthcare and beyond
- Covers both digital and analog signals
- An indispensable resource for tech writers, marketers, managers, and other nonengineers
The Complete DSP Guide for Businesspeople and Nontechnical Professionals
Digital signal processing (DSP) technology is everywhere–each time you use a smartphone, tablet, or computer; play an MP3;...
Automatic Speech Recognition: A Deep Learning Approach (Signals and Communication Technology)
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
Statistical Methods for Speech Recognition (Language, Speech, and Communication)
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is...
A Self-Study Guide for Digital Signal Processing
The Study Guide is intended for use as a companion for self-study to the textbook entitled Digital Signal Processing, Principles, Algorithms, and Applications,Third Edition, published by Prentice Hall. MATLAB is incorporated as the basic software tool for this self-study guide. The Study Guide, along with the textbook, can be used by students, practicing engineers, and scientists who wish to obtain an introduction to the subject. It can also be used by people who have had a basic...
Pattern Classification (2nd Edition)
The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.
An Instructor's Manual presenting detailed solutions to all the...
Signal Processing First
Designed and written by experienced and well-respected authors, this hands on, multi-media package provides a motivating introduction to fundamental concepts, specifically discrete-time systems. Unique features such as visual learning demonstrations, MATLAB laboratories and a bank of solved problems are just a few things that make this an essential learning tool for mastering fundamental concepts in today's electrical and computer engineering forum. Covers basic DSP concepts, integrated...
Digital signal processing laboratory using MATLAB
"Digital Signal Processing Laboratory Using MATLAB" is intended for a computer-based DSP laboratory course that supplements a lecture course on Digital Signal Processing. The book can be used either as a stand-alone text or in conjunction with Mitra's "Digital Signal Processing: A Computer-Based Approach". The book includes 11 laboratory exercises, with each exercise containing a number of projects to be carried out on a computer. The book assumes that the reader has no background in MATLAB...
Digital Signal Processing: A Gentle Introduction with Audio Examples
This book describes what is meant by a digital signal, how to view, modify, and review signals using DSP. No mathematical background is needed.
Digital Signal Processing with Kernel Methods (Wiley - IEEE)
A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can...
Digital Signal Processing Using MATLAB: A Problem Solving Companion (Activate Learning with these NEW titles from Engine
Help your student learn to maximize MATLAB as a computing tool to explore traditional Digital Signal Processing (DSP) topics, solve problems and gain insights. An extremely valuable supplementary text, DIGITAL SIGNAL PROCESSING USING MATLAB: A PROBLEM SOLVING COMPANION, 4E greatly expands the range and complexity of problems that students can effectively study in your course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, they require a...
Think DSP: Digital Signal Processing in Python
Think DSP: Digital Signal Processing in Python is an introduction to signal processing and system analysis using a computational approach. The premise of this book (like the others in the Think X series) is that if you know how to program, you can use that skill to learn other things. By the end of the first chapter, you'll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Subsequent chapters follow a logical progression that develops the...
Bayesian Speech and Language Processing
With this comprehensive guide you will learn how to apply Bayesian machine learning techniques systematically to solve various problems in speech and language processing. A range of statistical models is detailed, from hidden Markov models to Gaussian mixture models, n-gram models and latent topic models, along with applications including automatic speech recognition, speaker verification, and information retrieval. Approximate Bayesian inferences based on MAP, Evidence, Asymptotic, VB, and...
Sparse Modeling: Theory, Algorithms, and Applications (Chapman & Hall/Crc Machine Learning & Pattern Recognition)
Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing.
Sparse Modeling: Theory, Algorithms, and Applications provides an introduction to the growing field of sparse modeling, including application examples, problem formulations that yield sparse solutions, algorithms for finding...
Automatic Speech Recognition: A Deep Learning Approach (Signals and Communication Technology)
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
The Essential Guide to Digital Signal Processing (Essential Guide Series)
¿
- How signal processing works: clear, simple explanations in plain English
- Breakthrough DSP applications: from smartphones to healthcare and beyond
- Covers both digital and analog signals
- An indispensable resource for tech writers, marketers, managers, and other nonengineers
The Complete DSP Guide for Businesspeople and Nontechnical Professionals
Digital signal processing (DSP) technology is everywhere–each time you use a smartphone, tablet, or computer; play an MP3;...
Schaums Outline of Digital Signal Processing, 2nd Edition (Schaum's Outline Series)
The ideal review for your digital signal processing course
More than 40 million students have trusted Schaum’s Outlines for their expert knowledge and helpful solved problems. Written by renowned experts in their respective fields, Schaum’s Outlines cover everything from math to science, nursing to language. The main feature for all these books is the solved problems. Step-by-step, authors walk readers through coming up with solutions to exercises in their topic of choice.
