This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. It examines the vital role signal processing plays in enabling a new generation of technology based on big data, and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Signal Processing: Innovation and Applications presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology.

Advances in Imaging and Electron Physics, Volume 224 highlights new advances in the field, with this new volume presenting interesting chapters on Measuring elastic deformation and orientation gradients by scanning electron microscopy - conventional, new and emerging methods, Development of an alternative global method with high angular resolution, Implementing the new global method, Numerical validation of the method and influence of optical distortions, and Applications of the method.

In two editions spanning more than a decade, The Electrical Engineering Handbook stands as the definitive reference to the multidisciplinary field of electrical engineering. Our knowledge continues to grow, and so does the Handbook. For the third edition, it has expanded into a set of six books carefully focused on a specialized area or field of study. Each book represents a concise yet definitive collection of key concepts, models, and equations in its respective domain, thoughtfully gathered for convenient access. Circuits, Signals, and Speech and Image Processing presents all of the basic information related to electric circuits and components, analysis of circuits, the use of the Laplace transform, as well as signal, speech, and image processing using filters and algorithms. It also examines emerging areas such as text-to-speech synthesis, real-time processing, and embedded signal processing. Each article includes defining terms, references, and sources of further information. Encompassing the work of the world's foremost experts in their respective specialties, Circuits, Signals, and Speech and Image Processing features the latest developments, the broadest scope of coverage, and new material on biometrics.

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.

This book is a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2020), held at Technical University of Sofia, Sofia, Bulgaria, during 09-11 July 2020. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many 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.

Advances in the availability of computing power gave rise to an explosion of interest in the applications of smart antennas. Their ability to receive, block, and transmit signals simultaneously and in different directions renders them useful in areas from medical imaging to submarine sonar. This book examines the properties and applications of smart antennas. Detailed chapters address signal models, narrowband and broadband processing, adaptive algorithms, preprocessing techniques, and much more. Smart Antennas not only provides an instrument of learning that brings newcomers to the field quickly up to speed, but it also serves as an outstanding source of reference for thousands of practicing engineers.

Based on years of instruction and field expertise, this volume offers the necessary tools to understand all scientific, computational, and technological aspects of speech processing. The book emphasizes mathematical abstraction, the dynamics of the speech process, and the engineering optimization practices that promote effective problem solving in this area of research and covers many years of the authors' personal research on speech processing. Speech Processing helps build valuable analytical skills to help meet future challenges in scientific and technological advances in the field and considers the complex transition from human speech processing to computer speech processing.

Additive manufacturing (AM) and subtractive manufacturing (SM) offer numerous advantages in the production of single and multiple components. They provide incomparable design independence and are used to fabricate products in several industries, e.g.: aeronautic, automotive, biomedical, etc. The book presents recent results of processes including 3D printing, SLS (selective laser sintering), EBM (electron beam melting) and Precise Cutting and Drilling.

The book illustrates the theoretical results of fractional derivatives via applications in signals and systems, covering continuous and discrete derivatives, and the corresponding linear systems. Both time and frequency analysis are presented. Some advanced topics are included like derivatives of stochastic processes. It is an essential reference for researchers in mathematics, physics, and engineering.

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.

Describing non-parametric and parametric theoretic classification and the training of discriminant functions, this second edition includes new and expanded sections on neural networks, Fisher's discriminant, wavelet transform, and the method of principal components. It contains discussions on dimensionality reduction and feature selection, novel computer system architectures, proven algorithms for solutions to common roadblocks in data processing, computing models including the Hamming net, the Kohonen self-organizing map, and the Hopfield net, detailed appendices with data sets illustrating key concepts in the text, and more.

Contents:
PartI: Multidimensional Systems - General 1. Two Decades of Multidimensional Systems Research and Future Trends 2. MATLAB Package for n-D Sampling-Based Modelling of Nonlinear Systems 3. Behaviours, Modules, and Duality. Part II: Control of Multidimensional Systems and Applications 4. Output Feedback Stabilizability and Stabilization of Linear n-D Systems 5. A Review of n-D System Control Theory in a Certain Practical Sense 6. Two Decades of Research on Linear Repetitive Processes 7. Analysis and Control of Discrete Linear Repetitive Processes with Dynamic Boundary Conditions 8. Entire Function Methods for Optimisation Problems in Continuous-Discrete 2D Control Systems 9. Existence of an Optimal Solution for a Continuous Roesser Problem with a Terminal Condition. Part III: Multidimensional Circuits and Signal Processing 10. On The Structure of Linear Phase Perfect Reconstruction Quincunx Filter Banks 11. Deadbands in m-D Delta Operator Based Digital Filters with Floating Point Arithmetic 12. Cascade Synthesis of Two-Variable Lossless Two-Port Networks with Lumped Elements and Transmission Lines: A Semi-Analytic Procedure 13. Reconstruction of Positron Emission Tomography Images by Using MAP Estimation 14. Inspection of Fixing Devices of Railroad Lines Using Image Processing Algorithms 15. Increase of Frame Rate in Virtual Environments by Using 2D Image Warping

This book offers a user friendly, hands-on, and systematic introduction to applied and computational harmonic analysis: to Fourier analysis, signal processing and wavelets; and to their interplay and applications. The approach is novel, and the book can be used in undergraduate courses, for example, following a first course in linear algebra, but is also suitable for use in graduate level courses. The book will benefit anyone with a basic background in linear algebra. It defines fundamental concepts in signal processing and wavelet theory, assuming only a familiarity with elementary linear algebra. No background in signal processing is needed. Additionally, the book demonstrates in detail why linear algebra is often the best way to go. Those with only a signal processing background are also introduced to the world of linear algebra, although a full course is recommended. The book comes in two versions: one based on MATLAB, and one on Python, demonstrating the feasibility and applications of both approaches. Most of the MATLAB code is available interactively. The applications mainly involve sound and images. The book also includes a rich set of exercises, many of which are of a computational nature.

Summarizing the latest research results for mitigating intersymbol interference (ISI), this pioneering reference/text introduces the new technique of modulated coding (MC) and considers three cases of MC encoding and decoding in which ISI channel information is: 1) available for both encoding and decoding, 2) not available for either encoding or decoding, and 3) available for encoding but not for decoding. Includes previously unpublished information and open problems on MC for ISI channels Focusing on transmitter-assisted equalization methods for ISI mitigation, Modulated Coding for Intersymbol Interference Channels reviews current ISI mitigation methods and formulates the capacity and information rates of an ISI channel details basic concepts related to MC and describes the combination of an MC and an ISI channel compares the coding of an MC and ISI channel to that of an uncoded Additive White Gaussian Noise (AWGN) channel considers the case of joint maximum-likelihood sequence estimation (MLSE) encoding and decoding of an MC coded ISI channel illustrates situations of suboptimal MC design given an ISI channel, such as Zero-Forcing Decision Feedback Equalizer (ZF-DFE) and Minimum Mean Square Error Decision Feedback Equalizer (MMSE-DFE) with corresponding MC designs considers multiple transmit and multiple receive antenna systems studies a channel-independent MC-coded orthogonal frequency division multiplexing (OFDM) system and also covers vector OFDM systems analyzes and applies polynomial ambiguity resistant MC (PARMC) to single-antenna and multiple-antenna systems and more Illustrated with over 900 equations and drawings, Modulated Coding for Intersymbol Interference Channels makes an excellent reference for electrical, electronics, signal processing, mechanical, image filtering and processing, computer circuit and systems, digital design, and communication engineers; and applied mathematicians; and a useful text

This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Third International Conference on Soft Computing and Signal Processing (ICSCSP 2020). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.

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.

While voice is widely used in speech recognition and speaker identification, its application in biomedical fields is much less common. This book systematically introduces the authors' research on voice analysis for biomedical applications, particularly pathological voice analysis. Firstly, it reviews the field to highlight the biomedical value of voice. It then offers a comprehensive overview of the workflow and aspects of pathological voice analysis, including voice acquisition systems, voice pitch estimation methods, glottal closure instant detection, feature extraction and learning, and the multi-audio fusion approaches. Lastly, it discusses the experimental results that have shown the superiority of these techniques. This book is useful to researchers, professionals and postgraduate students working in fields such as speech signal processing, pattern recognition, and biomedical engineering. It is also a valuable resource for those involved in interdisciplinary research.

Addresses a wide selection of multimedia applications, programmable and custom architectures for the implementations of multimedia systems, and arithmetic architectures and design methodologies. The book covers recent applications of digital signal processing algorithms in multimedia, presents high-speed and low-priority binary and finite field arithmetic architectures, details VHDL-based implementation approaches, and more.

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.

This book provides an in-depth coverage of the most recent developments in the field of wireless underground communications, from both theoretical and practical perspectives. The authors identify technical challenges and discuss recent results related to improvements in wireless underground communications and soil sensing in Internet of Underground Things (IOUT). The book covers both existing network technologies and those currently in development in three major areas of SitS: wireless underground communications, subsurface sensing, and antennas in the soil medium. The authors explore novel applications of Internet of Underground Things in digital agriculture and autonomous irrigation management domains. The book is relevant to wireless researchers, academics, students, and decision agriculture professionals. The contents of the book are arranged in a comprehensive and easily accessible format. Focuses on fundamental issues of wireless underground communication and subsurface sensing; Includes advanced treatment of IOUT custom applications of variable-rate technologies in the field of decision agriculture, and covers protocol design and wireless underground channel modeling; Provides a detailed set of path loss, antenna, and wireless underground channel measurements in various novel Signals in the Soil (SitS) testbed settings.