The parameter estimation and hypothesis testing are the basic tools in statistical inference. These techniques occur in many applications of data processing., and methods of Monte Carlo have become an essential tool to assess performance. For pedagogical purposes the book includes several computational problems and exercices. To prevent students from getting stuck on exercises, detailed corrections are provided.

This textbook presents an introduction to signal processing for audio applications. The author's approach posits that math is at the heart of audio processing and that it should not be simplified. He thus retains math as the core of signal processing and includes concepts of difference equations, convolution, and the Fourier Transform. Each of these is presented in a context where they make sense to the student and can readily be applied to build artifacts. Each chapter in the book builds on the previous ones, building a linear, coherent story. The book starts with a definition of sound and goes on to discuss digital audio signals, filters, The Fourier Transform, audio effects, spatial effects, audio equalizers, dynamic range control, and pitch estimation. The exercises in each chapter cover the application of the concepts to audio signals. The exercises are made specifically for Pure Data (Pd) although traditional software, such as MATLAB, can be used. The book is intended for students in media technology bachelor programs. The book is based on material the author developed teaching on the topic over a number of years.

This volume is an extended description of continuous-time signals related to the course of Signals and Systems. As a time-varying process of any physical state of any object, which serves for representation, detection, and transmission of messages, a modern electrical signal possesses, in applications, many specific properties. To make possible for readers to deal with signals free, the book systematically covers major principle foundations of the signals theory. The representation of signals in the frequency domain (by Fourier transform) is considered with strong emphasis on how the spectral density of a single waveform becomes that of its burst and then the spectrum of its train. Different kinds of amplitude and angular modulations are analyzed noticing a consistency between the spectra of modulating and modulated signals. The energy and power presentation of signals is given along with their correlation properties.

Optimal and Adaptive Signal Processing covers the theory of optimal and adaptive signal processing using examples and computer simulations drawn from a wide range of applications, including speech and audio, communications, reflection seismology and sonar systems. The material is presented without a heavy reliance on mathematics and focuses on one-dimensional and array processing results, as well as a wide range of adaptive filter algorithms and implementations. Topics discussed include random signals and optimal processing, adaptive signal processing with the LMS algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing.

Optimal and Adaptive Signal Processing is a valuable guide for scientists and engineers, as well as an excellent text for senior undergraduate/graduate level students in electrical engineering.

This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing. The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields. Key Features: * Aimed at random signal processing with parametric signal processing-using appropriate segment size. * Covers speech, image, medical images, EEG and ECG signal processing. * Reviews optimal detection and estimation. * Discusses parametric modeling and signal processing in transform domain. * Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions

This book is primarily intended for junior-level students who take the courses on 'signals and systems'. It may be useful as a reference text for practicing engineers and scientists who want to acquire some of the concepts required for signal proce- ing. The readers are assumed to know the basics about linear algebra, calculus (on complex numbers, differentiation, and integration), differential equations, Laplace R transform, and MATLAB . Some knowledge about circuit systems will be helpful. Knowledge in signals and systems is crucial to students majoring in Electrical Engineering. The main objective of this book is to make the readers prepared for studying advanced subjects on signal processing, communication, and control by covering from the basic concepts of signals and systems to manual-like introduc- R R tions of how to use the MATLAB and Simulink tools for signal analysis and lter design. The features of this book can be summarized as follows: 1. It not only introduces the four Fourier analysis tools, CTFS (continuous-time Fourier series), CTFT (continuous-time Fourier transform), DFT (discrete-time Fourier transform), and DTFS (discrete-time Fourier series), but also illuminates the relationship among them so that the readers can realize why only the DFT of the four tools is used for practical spectral analysis and why/how it differs from the other ones, and further, think about how to reduce the difference to get better information about the spectral characteristics of signals from the DFT analysis.

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

Presents basic theories, techniques, and procedures used to analyze, design, and implement two-dimensional filters; and surveys a number of applications in image and seismic data processing that demonstrate their use in real-world signal processing. For graduate students in electrical and computer e

This "bible" of a whole generation of communications engineers was originally published in 1958. The focus is on the statistical theory underlying the study of signals and noises in communications systems, emphasizing techniques as well s results. End of chapter problems are provided.
Sponsored by:
IEEE Communications Society

For upper-level undergraduate courses in deterministic and stochastic signals and system engineering An Integrative Approach to Signals, Systems and Inference Signals, Systems and Inference is a comprehensive text that builds on introductory courses in time- and frequency-domain analysis of signals and systems, and in probability. Directed primarily to upper-level undergraduates and beginning graduate students in engineering and applied science branches, this new textbook pioneers a novel course of study. Instead of the usual leap from broad introductory subjects to highly specialised advanced subjects, this engaging and inclusive text creates a study track for a transitional course. Properties and representations of deterministic signals and systems are reviewed and elaborated on, including group delay and the structure and behavior of state-space models. The text also introduces and interprets correlation functions and power spectral densities for describing and processing random signals. Application contexts include pulse amplitude modulation, observer-based feedback control, optimum linear filters for minimum mean-square-error estimation, and matched filtering for signal detection. Model-based approaches to inference are emphasised, in particular for state estimation, signal estimation, and signal detection.

Your cutting-edge introduction to radar signal processing-fully updated for the latest advances This up-to-date guide provides in-depth coverage of the full breadth of foundational radar signal processing methods of waveform design, Doppler processing, detection, tracking, imaging, and adaptive processing from a digital signal processing perspective. The techniques of linear systems, filtering, sampling, and Fourier analysis are used throughout to provide a unified tutorial approach. Developed from the author's extensive academic and professional experience, Fundamentals of Radar Signal Processing, Third Edition has been revised and updated throughout. Readers will find the solid foundations of earlier editions enhanced with new material on such topics as keystone formatting, detection in spiky clutter, range migration and backprojection imaging, virtual arrays, ground moving target indication, and many more. Presents complete coverage of foundational digital radar signal processing techniques Integrates linear FMCW techniques of emerging fields such as automotive radar with pulsed methods Includes additional homework problems in all chapters Comes with an online suite of answer keys, solutions manuals, tutorial MATLAB demos, and technical notes

Adaptive Control (second edition) shows how a desired level of system performance can be maintained automatically and in real time, even when process or disturbance parameters are unknown and variable. It is a coherent exposition of the many aspects of this field, setting out the problems to be addressed and moving on to solutions, their practical significance and their application. Discrete-time aspects of adaptive control are emphasized to reflect the importance of digital computers in the application of the ideas presented. The second edition is thoroughly revised to throw light on recent developments in theory and applications with new chapters on: multimodel adaptive control with switching, direct and indirect adaptive regulation and adaptive feedforward disturbance compensation. Many algorithms are newly presented in MATLAB (R) m-file format to facilitate their employment in real systems. Classroom-tested slides for instructors to use in teaching this material are also now provided. All of this supplementary electronic material can be downloaded from fill in URL. The core material is also up-dated and re-edited to keep its perspective in line with modern ideas and more closely to associate algorithms with their applications giving the reader a solid grounding in: synthesis and analysis of parameter adaptation algorithms, recursive plant model identification in open and closed loop, robust digital control for adaptive control; * robust parameter adaptation algorithms, practical considerations and applications, including flexible transmission systems, active vibration control and broadband disturbance rejection and a supplementary introduction on hot dip galvanizing and a phosphate drying furnace. Control researchers and applied mathematicians will find Adaptive Control of significant and enduring interest and its use of example and application will appeal to practitioners working with unknown- and variable-parameter plant. Praise for the first edition: ...well written, interesting and easy to follow, so that it constitutes a valuable addition to the monographies in adaptive control for discrete-time linear systems... suitable (at least in part) for use in graduate courses in adaptive control.

Often WT systems employ the discrete wavelet transform, implemented on a digital signal processor. However, in ultra low-power applications such as biomedical implantable devices, it is not suitable to implement the WT by means of digital circuitry due to the relatively high power consumption associated with the required A/D converter. Low-power analog realization of the wavelet transform enables its application in vivo, e.g. in pacemakers, where the wavelet transform provides a means to extremely reliable cardiac signal detection.

In Ultra Low-Power Biomedical Signal Processing we present a novel method for implementing signal processing based on WT in an analog way. The methodology presented focuses on the development of ultra low-power analog integrated circuits that implement the required signal processing, taking into account the limitations imposed by an implantable device.

The many intriguing examples on the application of mechatronics reinforce the excitement of this creative field of technology. As a collection they present a stimulating resource to developers of future mechatronics technology, and to educators searching for interesting examples. From structured-light measurement of the build-up of detritus on railway bogies and detection of uncracked spores of Chinese medicine to a practical tractor vision guidance system embedded in a smart-phone application, the practical applications of mechatronics and machine vision abound. Fruits are counted on the tree, pasture biomass is measured and a robot collects camel dung as a resource. 3D printing is in vogue, but papers here discuss the construction and strategy of the printer itself. The measurement and analysis of myoelectric muscle signals enable a prosthesis to be controlled and a feeding robot is used for patient care. An exoskeleton has both soft and rigid links and an optical sensor analyses the tissue into which a surgical needle is being inserted. These are some of the papers in this collection from the 26th annual conference on Mechatronics and Machine Vision in Practice, carefully selected to exclude papers that are merely theoretical and to highlight those that show practical verification. Papers have been contributed from China, New Zealand, the Philippines, Emirates, Germany and of course Australia.

The current popular and scientific interest in virtual environments has provided a new impetus for investigating binaural and spatial hearing. However, the many intriguing phenomena of spatial hearing have long made it an exciting area of scientific inquiry. Psychophysical and physiological investigations of spatial hearing seem to be converging on common explanations of underlying mechanisms. These understandings have in turn been incorporated into sophisticated yet mathematically tractable models of binaural interaction. Thus, binaural and spatial hearing is one of the few areas in which professionals are soon likely to find adequate physiological explanations of complex psychological phenomena that can be reasonably and usefully approximated by mathematical and physical models. This volume grew out of the Conference on Binaural and Spatial Hearing, a four-day event held at Wright-Patterson Air Force Base in response to rapid developments in binaural and spatial hearing research and technology. Meant to be more than just a proceedings, it presents chapters that are longer than typical proceedings papers and contain considerably more review material, including extensive bibliographies in many cases. Arranged into topical sections, the chapters represent major thrusts in the recent literature. The authors of the first chapter in each section have been encouraged to take a broad perspective and review the current state of literature. Subsequent chapters in each section tend to be somewhat more narrowly focused, and often emphasize the authors' own work. Thus, each section provides overview, background, and current research on a particular topic. This book is significant in that it reviews the important work during the past 10 to 15 years, and provides greater breadth and depth than most of the previous works.

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A no-nonsense guide to the fundamentals and applications of statistical signal processing Ideal for upper-undergraduate and graduate courses, this engineering textbook offers key signal analysis principles and uses and explains the necessary underlying mathematics. Coverage includes representation and approximation theory in vector spaces, the orthogonality principle, the least squares problem, minimum mean square estimation, and the Wiener-Hopf equation. Signal Analysis: A Concise Guide clearly explains linear systems and signals and the concepts behind them. The book covers matrix factorizations, optimal linear filter theory, classical and modern spectral estimation, adaptive filters, and processing of spatial arrays. You will also explore linear optima filters, eigrn decomposition methods, the singular value decomposition, adaptive linear filters, noise cancellation, and spectral estimation. * Includes exercises for computer implementation using MATLAB * Presents the core material in a succinct format * Written by a team of renowned academics with multiple teaching awards

Design and MATLAB concepts have been integrated in text.
* Integrates applications as it relates signals to a remote sensing system, a controls system, radio astronomy, a biomedical system and seismology.

This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020. The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.

Provides Typical Abstract Representations of Different Steps for Analyzing Any Dynamic System Vibration and dynamics are common in everyday life, and the use of vibration measurements, tests, and analyses is becoming standard for various applications. Vibration Analysis, Instruments, and Signal Processing focuses on the basic understanding of vibration measurements and analysis. This book covers different areas of vibration measurements and analysis needed in practice, and discusses theory, application, and a variety of methods, in a simplified way. It communicates the fundamental principles of all three facets of vibration-based analysis, and highlights four major points-theory, instruments, experiments, and signal processing. Useful for everyday work, the book dedicates several chapters to the day-to-day requirements involved in vibration measurements and analysis, and addresses a number of topics useful for many day-to-day analyses and experiments. The book provides experimental examples in each chapter-considering basic theories and analysis methods, instrumentations and signal processing methods, and combined analysis-as well as experimental approaches and case studies. In addition, it dedicates a complete chapter to case studies relating the basic theory, types of instruments and measurements needed, and requisite signal processing that ultimately result in a final diagnosis. Consisting of ten chapters, this informative text: Provides the basic understanding and concept of the vibration theory, mathematical modeling of structures and machines using the finite element (FE) method, and the vibration response computation using the FE model for the load applied Discusses a simplified vibration theory through a single degree of freedom (SDOF) system of a mass and a spring Introduces the concept of FE modeling at a very basic level through a few simple examples Explores how the equation of motion in matrix form for any system can be integrated to solve for the responses at all DOFs due to the time-varying external loadings Developed for diverse audiences interested in vibration analysis, this book is suitable for every level of student, engineer, and scientist associated with vibration, structural and rotor dynamics, vibration-based diagnosis, and vibration-based condition monitoring.

In the past few years we have written and edited several books in the area of acousticandspeechsignalprocessing. Thereasonbehindthisendeavoristhat there were almost no books available in the literature when we ?rst started while there was (and still is) a real need to publish manuscripts summarizing the most useful ideas, concepts, results, and state-of-the-art algorithms in this important area of research. According to all the feedback we have received so far, we can say that we were right in doing this. Recently, several other researchers have followed us in this journey and have published interesting books with their own visions and perspectives. The idea of writing a book on Microphone Array Signal Processing comes from discussions we have had with many colleagues and friends. As a c- sequence of these discussions, we came up with the conclusion that, again, there is an urgent need for a monograph that carefully explains the theory and implementation of microphone arrays. While there are many manuscripts on antenna arrays from a narrowband perspective (narrowband signals and narrowband processing), the literature is quite scarce when it comes to s- sor arrays explained from a truly broadband perspective. Many algorithms for speech applications were simply borrowed from narrowband antenna - rays. However, a direct application of narrowband ideas to broadband speech processing may not be necessarily appropriate and can lead to many m- understandings.

Biomedical / Electrical Engineering Nonlinear Biomedical Signal Processing Volume II: Dynamic Analysis and Modeling A volume in the IEEE Press Series on Biomedical Engineering Metin Akay, Series Editor Featuring current contributions by experts in signal processing and biomedical engineering, this book introduces the concepts, recent advances, and implementations of nonlinear dynamic analysis methods. Together with Volume I in this series, this book provides comprehensive coverage of nonlinear signal and image processing techniques. Nonlinear Biomedical Signal Processing: Volume II combines analytical and biological expertise in the original mathematical simulation and modeling of physiological systems. Detailed discussions of the analysis of steady-state and dynamic systems, discrete-time system theory, and discrete modeling of continuous-time systems are provided. Biomedical examples include the analysis of the respiratory control system, the dynamics of cardiac muscle and the cardiorespiratory function, and neural firing patterns in auditory and vision systems. Examples include relevant MATLAB(r) and Pascal programs. Topics covered include:
* Nonlinear dynamics
* Behavior and estimation
* Modeling of biomedical signals and systems
* Heart rate variability measures, models, and signal assessments
* Origin of chaos in cardiovascular and gastric myoelectrical activity
* Measurement of spatio-temporal dynamics of human epileptic seizures.
A valuable reference book for medical researchers, medical faculty, and advanced graduate students, it is also essential reading for practicing biomedical engineers. Nonlinear Biomedical Signal Processing, Volume II is anexcellent companion to Dr. Akay's Nonlinear Biomedical Signal Processing, Volume I: Fuzzy Logic, Neural Networks, and New Algorithms.

This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring and in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.

With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility. Fundamentals, Algorithms, Evaluation, and Future Steps Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions. What's New in This Edition Updates in every chapter A new chapter on objective speech intelligibility measures A new chapter on algorithms for improving speech intelligibility Real-world noise recordings (on downloadable resources) MATLAB (R) code for the implementation of intelligibility measures (on downloadable resources) MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on downloadable resources) Valuable Insights from a Pioneer in Speech Enhancement Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise. Includes downloadable resources with Code and Recordings The downloadable resources provide MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms.

"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 important ideas incrementally, with a focus on applications.

"An excellent introductory book" (Review of the First Edition in the International Journal of Electrical Engineering Education) "…it will serve as a reference book in this area for a long time" (Review of Revised Edition in Zentralblatt für Mathematik (Germany))

Firmly established over the last decade as the essential introductory Digital Signal Processing (DSP) text, this second edition reflects the growing importance of random digital signals and random DSP in the undergraduate syllabus by including two new chapters. The authors’ practical, problem-solving approach to DSP continues in this new material, which is packed up by additional worked examples and computer programs. The book now features:

• fundamentals of digital signals and systems
• time and frequency domain analysis and processing, including digital convolution and the Discrete and Fast Fourier Transforms
• design and practical application of digital filters
• description and processing of random signals, including correlation, filtering, and the detection of signals in noise