Written by a working scientist/engineer who has used DSP in his inventions and designs, this book will help design engineers on the job trying to master a tough subject that is now regarded as an essential engineering skill and put it to use.

This book aims at undergraduate students who have basic knowledge in C programming, Circuit Theory, Systems and Simulations, and Spectral Analysis, focuses on basic concepts of digital signal processing, MATLAB simulation and implementation.

This book is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment, with Fourier series, matrices, probability, and statistics, etc.

This book introduces the mathematical models used to design and understand both Signals and Systems. Developing a deep understanding of how to digitally create and manipulate signals to measure and control the physical world and communication.

This book differs from the classical DSP book model pioneered by O/S. Includes chapters on DFT, Z-Transform and Filter Design. The book starts out with what one reviewer calls "fun topics", and DSP applications".

Digital signals place great demands on processing power, network bandwidth, storage capacity, I/O speed, and software design. As a result, signal computing is a great laboratory for exercising the full range of knowledge of computer science.

This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications.

This book is an introduction to signal processing and system analysis using a computational approach with Python as the programming language. It develops the important ideas incrementally, with a focus on applications.

This textbook acts as a hands-on introduction to the areas of Digital Signal Processing (DSP), Software-Defined Radio (SDR), and wireless communications. Think of this textbook like a gateway into the world of DSP and SDR.

This book is an introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Juptyer Notebook so that you can run and modify the code in your browser. What better way to learn?

This book presents an exhaustive and detailed account of Window Functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing.

This book, together with its predecessor Foundations of Signal Processing, presents a thorough introduction to the mathematical foundations of signal and image processing using Fourier and Wavelet Transforms.

This book provides an application-based approach using real-world examples to illustrate the application of sensor technologies in a practical and experiential manner, especially in healthcare, wellness, and environmental monitoring.

Microsensor is a very small sensor with physical dimensions in the submicrometer to millimeter range. The objective of the book is to provide topics in the area of microsensors for engineers, scientists, applied physicists.

This book was developed for the course "Signal Processing Models in Musical Acoustics". The course was created for graduate students in computer music and engineering interested in efficient computational modeling of musical instruments.

Conceived to be available to a wide audience, the aim of this book is to provide a guide to the latest advances in emerging issues in the design and implementation of DSP systems for application-specific circuits and programmable devices.

This work is primarily on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis; consequently.

Presents advanced developments in digital filters and signal process methods covering different cases studies with the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed widely.

This book is a hands-on introduction to computer vision using Python. It gives an easily accessible entry point to hands-on computer vision with enough understanding of the underlying theory and algorithms to be a foundation for students, researchers.

Almost all textbooks on signal processing have a section devoted to the Fourier transform theory. For this reason, this book focuses on the Fourier transform applications in signal processing techniques.

Inexpensive and rapid computational power provided powerful tools to overcome the limitations of current technologies and enabled us to apply several advanced statistical signal processing techniques.

Describes the latest research in applying signal processing methodologies in the context of emerging and future wireless applications, such as next-generation cellular telephony, nomadic computing, and wireless media.

A unique feature of this book is its integration with the statistical software package SAS (Statistical Analysis System) computing environment. Basic applied statistics is assumed through multiple regression.

It describes fundamental signal and image processing techniques that are used to process biomedical information, discusses applications of techniques in the processing of main biomedical signals and images, such as EEG, ECG, MRI, and CT.

It provides an understanding of biological signals and digital signal analysis techniques such as conditioning, filtering, feature extraction, classification and statistical validation for solving practical biological signal analysis problems using MATLAB.

This book describes the essential tools and techniques of statistical signal processing, with specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, etc.

Signal processing is ubiquitous in modern technology. Its mathematical basis and applications are the subject of this book. Emphasis is on challenges, new techniques adapted to new technologies, and certainrecent advances in algorithms and theory.

This book describes some of the technical methods and systems used for document processing of text and graphics images. The methods have grown out of the fields of digital signal processing, digital image processing, and pattern recognition.

This e-course is designed to give the people who are interested in image processing the fundamental concepts in digital image processing with emphasis in sampling, quantization, interpolation, filtering, and spatial domain enhancement.

This book is a tutorial on image processing. Each chapter explains basic concepts with words and figures, shows image processing results with photographs, and implements the operations in C.

Provide you with different theorethical and practical approaches to digital filter design. It covers design of both finite and infinite impulse response filters. In addition, it applies the most popular and most commonly used design methodes giving the best solutions.

This note primarily addresses how to estimate impulse response lengths short of actually designing the filter itself and indirectly discusses a bit the first. It examines how to convert a typical filter specification in terms of cutoff frequency, passband ripple, etc.

Taking a novel, less classical approach to the subject, the authors have written this book with the conviction that signal processing should be fun. Their treatment is less focused on the mathematics and more on the conceptual aspects.

Mixed-signal processing implies the use of both analog and digital in the same system. The reader is provided with information on how to choose between the techniques and how to design a system that takes advantage of the best features of each of them.

A digital filter can be pictured as a "black box" that accepts a sequence of numbers and emits a new sequence of numbers. This book is a gentle introduction to digital filters, including mathematical theory, illustrative examples, some audio applications, and useful software starting points.

This book has been structured around the Next Generation Network (NGN) framework, which separates the transport network, services, and signaling protocols into the service stratum and the transport stratum.

Detailed derivation of the Discrete Fourier Transform (DFT) and its associated mathematics, including elementary audio signal processing applications and matlab programming examples.

This book focuses on the Discrete Fourier Transform (DFT), discrete convolution, and, particularly, the fast algorithms to calculate them. Topics on digital signal processing since its beginning, and new results in hardware, theory and applications, etc.

Image analysis and processing is steadily gaining relevance within the large number of application fields to which genetic and evolutionary computation (GEC) techniques are applied. This book is the first attempt to offer a panoramic view on the field.

This book is a one-stop engineering reference. Covering data converter fundamentals, techniques, applications, and beginning with the basic theoretical elements necessary for a complete understanding of data converters, this reference covers all the latest advances.

This is an outstanding and often overlooked book on optimal signal processing. The author does an excellent job relating the filtering problem to optimization in linear spaces and then shows how this is related to the optimal correlation canceller.

Sound manipulation is an activity that find an increasing number of practitioners in the fields of artistic expression, technology, and science. This book is aimed at providing such language and mathematical, algorithmic, and computational tools.

One can say that human hearing occurs in terms of spectral models. As a result, spectral models are especially useful in audio applications. This is the basis of modern audio compression techniques. The chapters are organized in a progression from basic spectrum analysis to more advanced frequency-domain signal processing.

This book provides the first general framework, based on universal statistical properties of natural images, of detecting tampering and authenticating digital images that has been successfully applied to three problems in digital image forensics.

This book has provided a step-by-step guide to programming these microcontrollers (MCUs) with the C programming language.

This book will help you learn more about programming PIC microcontrollers in BASIC with practical, common-sense instructions, real projects, etc.

The book provides numerous practical examples with necessary connection schematics explaining the operation of temperature sensors, A/D and D/A converters, LCD and LED displays, relays, communication modules etc.