Synthesis of Computational Structures for Analog Signal Processing focuses on analysis and design of analog signal processing circuits. The author presents a multitude of design techniques for improving the performances of analog signal processing circuits, and proposes specific implementation strategies that can be used in CMOS technology. The author's discussion proceeds from the perspective of signal processing as it relates to analog. Included are coverage of low-power design, portable equipment, wireless nano-sensors and medical implantable devices.
The material is especially appropriate for researchers and specialists in the area of analog and mixed-signal CMOS VLSI design, as well as postgraduate or Ph.D. students working on analog microelectronics.

Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation.

Wavelet analysis is among the newest additions to the arsenals of mathematicians, scientists, and engineers, and offers common solutions to diverse problems. However, students and professionals in some areas of engineering and science, intimidated by the mathematical background necessary to explore this subject, have been unable to use this powerful tool.

The first book on the topic for readers with minimal mathematical backgrounds, Wavelet Analysis with Applications to Image Processing provides a thorough introduction to wavelets with applications in image processing. Unlike most other works on this subject, which are often collections of papers or research advances, this book offers students and researchers without an extensive math background a step-by-step introduction to the power of wavelet transforms and applications to image processing.
The first four chapters introduce the basic topics of analysis that are vital to understanding the mathematics of wavelet transforms. Subsequent chapters build on the information presented earlier to cover the major themes of wavelet analysis and its applications to image processing. This is an ideal introduction to the subject for students, and a valuable reference guide for professionals working in image processing.

The book systematically introduces theories of frequently-used modern signal processing methods and technologies, and focuses discussions on stochastic signal, parameter estimation, modern spectral estimation, adaptive filter, high-order signal analysis and non-linear transformation in time-domain signal analysis. With abundant exercises, the book is an essential reference for graduate students in electrical engineering and information science.

This text presents a comprehensive treatment of signal processing and linear systems suitable for undergraduate students in electrical engineering, It is based on Lathi's widely used book, Linear Systems and Signals, with additional applications to communications, controls, and filtering as well as new chapters on analog and digital filters and digital signal processing.This volume's organization is different from the earlier book. Here, the Laplace transform follows Fourier, rather than the reverse; continuous-time and discrete-time systems are treated sequentially, rather than interwoven. Additionally, the text contains enough material in discrete-time systems to be used not only for a traditional course in signals and systems but also for an introductory course in digital signal processing. In Signal Processing and Linear Systems Lathi emphasizes the physical appreciation of concepts rather than the mere mathematical manipulation of symbols. Avoiding the tendency to treat engineering as a branch of applied mathematics, he uses mathematics not so much to prove an axiomatic theory as to enhance physical and intuitive understanding of concepts. Wherever possible, theoretical results are supported by carefully chosen examples and analogies, allowing students to intuitively discover meaning for themselves.

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to "experiment and learn" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

This book provides the reader with empirical findings on innovative signal processing approaches to detecting pathologies in infant cries, by comparing new technological approaches to standard ones. The contributors examine novel approaches to machine adaptation to dysarthric speech.

This book discusses statistical modeling of single- and multi-channel synthetic aperture radar (SAR) images and the applications of these newly developed models in land and ocean monitoring, such as target detection and terrain classification. It is a valuable reference for researchers and engineers interested in information processing of remote sensing, radar signal processing, and image interpretation.

This book covers newly developed and novel Steganography techniques and algorithms. The book outlines techniques to provide security to a variety of applications using Steganography, with the goal of both hindering an adversary from decoding a hidden message, and also preventing an adversary from suspecting the existence of covert communications. The book looks into applying these newly designed and improved algorithms to provide a new and efficient Steganographic system, called Characteristic Region-Based Image Steganography (CR-BIS). The algorithms combine both the robustness of the Speeded-Up Robust Features technique (SURF) and Discrete Wavelet Transform (DWT) to achieve characteristic region Steganography synchronization. The book also touches on how to avoid hiding data in the whole image by dynamically selecting characteristic regions for the process of embedding. Applies and discusses innovative techniques for hiding text in a digital image file or even using it as a key to the encryption; Provides a variety of methods to achieve characteristic region Steganography synchronization; Shows how Steganography improves upon cryptography by using obscurity features.

Starting with an overview of current research progresses on multiple access technology, the book then presents the theoretical fundamentals, technical principles, transmission scheme, key technologies and evaluation results of new multi-access technologies, especially focusing on its typical applications 5G communication systems. With extensive practical cases, it is an essential reference for researchers, engineers and graduate students.

A readable, understandable introduction to DSP for professionals and students alike . . .

This practical guide is a welcome alternative to more complicated introductions to DSP. It assumes no prior DSP experience and takes the reader step-by-step through the most basic signal processing concepts to more complex functions and devices, including sampling, filtering, frequency transforms, data compression, and even DSP design decisions. The guide provides clear, concise explanations and examples, while keeping mathematics to a minimum, to help develop a fundamental understanding of DSP.

Other features include:

• An extensive resource bibliography of more advanced DSP books.
• An example of a typical DSP system development cycle, including tool descriptions.
• A complete glossary of DSP-related acronyms

Whether you're a working engineer looking into DSP for the first time or an undergraduate struggling to comprehend the subject, this engaging introduction provides easy access to the basic knowledge that will lead to more advanced material.

Texas Instruments has been designing and manufacturing single-chip DSP devices since 1982 and now produces eight distinct generations as part of the industry-standard TMS320 family. Much of this book is based on the experience TI gained in developing DSPs and training first-time users.

With this groundbreaking text, discover how wireless artificial intelligence (AI) can be used to determine position at centimeter level, sense motion and vital signs, and identify events and people. Using a highly innovative approach that employs existing wireless equipment and signal processing techniques to turn multipaths into virtual antennas, combined with the physical principle of time reversal and machine learning, it covers fundamental theory, extensive experimental results, and real practical use cases developed for products and applications. Topics explored include indoor positioning and tracking, wireless sensing and analytics, wireless power transfer and energy efficiency, 5G and next-generation communications, and the connection of large numbers of heterogeneous IoT devices of various bandwidths and capabilities. Demo videos accompanying the book online enhance understanding of these topics. Providing a unified framework for wireless AI, this is an excellent text for graduate students, researchers, and professionals working in wireless sensing, positioning, IoT, machine learning, signal processing and wireless communications.

This book provides the basic concepts and fundamental principles of dynamic systems including experimental methods, calibration, signal conditioning, data acquisition and processing as well as the results presentation. How to select suitable sensors to measure is also introduced. It is an essential reference to students, lecturers, professionals and any interested lay readers in measurement technology.

Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to large-scale data.

The book presents selected, extended and peer reviewed papers from the International Multiconference on System, Automation and Control held Leipzig in 2016. These are complemented with solicited contributions by international experts. This volume is devoted to power electronics in renewable energy systems as well as to hybrid renewable energy systems.

The book presents selected, extended and peer reviewed papers from the International Multiconference on System, Automation and Control held Leipzig in 2016. These are complemented with solicited contributions by international experts. Main topics are: mechanical and thermal sensors, nano sensors, optical, chemical and biomedical sensors. They are applied in energy harvesting, biomedical and environmental measurments and more.

A self-contained introduction to adaptive inverse control
Now featuring a revised preface that emphasizes the coverage of both control systems and signal processing, this reissued edition of Adaptive Inverse Control takes a novel approach that is not available in any other book.
Written by two pioneers in the field, Adaptive Inverse Control presents methods of adaptive signal processing that are borrowed from the field of digital signal processing to solve problems in dynamic systems control. This unique approach allows engineers in both fields to share tools and techniques. Clearly and intuitively written, Adaptive Inverse Control illuminates theory with an emphasis on practical applications and commonsense understanding. It covers: the adaptive inverse control concept; Weiner filters; adaptive LMS filters; adaptive modeling; inverse plant modeling; adaptive inverse control; other configurations for adaptive inverse control; plant disturbance canceling; system integration; Multiple-Input Multiple-Output (MIMO) adaptive inverse control systems; nonlinear adaptive inverse control systems; and more.
Complete with a glossary, an index, and chapter summaries that consolidate the information presented, Adaptive Inverse Control is appropriate as a textbook for advanced undergraduate- and graduate-level courses on adaptive control and also serves as a valuable resource for practitioners in the fields of control systems and signal processing.

This book offers an in-depth discussion related to metrological aspects of automated tests. The accuracy of experimental estimates of test object performance is examined from the standpoint of their statistical variance and systematic biases. The proposed metrological model of automated tests allows to determine the metrological characteristics of measurement means using data from their static and dynamic calibrations. Knowledge of these characteristics provides an ability to examine their impact on the accuracy of test results for the purposes of estimating statistical uncertainties caused by instrumentation errors and eliminating biases that occur as a consequence of inertial properties of measurement means. Optimization of requirements for measurement errors to ensure a given accuracy of test results is discussed as well. Proposed approaches and described methods are illustrated by test examples of turbomachinery products.

The book presents fundamentals of communication electronic circuits, including structure, principle, analyzing methodology, design and design software. Radio frequency amplifier, sinusoidal oscillator, amplitude modulation and demodulation, angular modulation and demodulation are described in detail. The book serves for learning and teaching but can also help researchers and professionals as reference.