Digital Signal Processing 101: Everything You Need to Know to Get Started provides a basic tutorial on digital signal processing (DSP). Beginning with discussions of numerical representation and complex numbers and exponentials, it goes on to explain difficult concepts such as sampling, aliasing, imaginary numbers, and frequency response. It does so using easy-to-understand examples with minimum mathematics. In addition, there is an overview of the DSP functions and implementation used in several DSP-intensive fields or applications, from error correction to CDMA mobile communication to airborne radar systems. This book has been updated to include the latest developments in Digital Signal Processing, and has eight new chapters on: Automotive Radar Signal Processing Space-Time Adaptive Processing Radar Field Orientated Motor Control Matrix Inversion algorithms GPUs for computing Machine Learning Entropy and Predictive Coding Video compression

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting.

Medical imaging is one of the heaviest funded biomedical engineering research areas. The second edition of Pattern Recognition and Signal Analysis in Medical Imaging brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data. Since the first edition, there has been tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer-aided analytical techniques, coupled with a continuing need to derive more information from medical images, has led to a growing application of digital processing techniques in cancer detection as well as elsewhere in medicine. This book is an essential tool for students and professionals, compiling and explaining proven and cutting-edge methods in pattern recognition for medical imaging.

The first book to combine satellite and terrestrial positioning techniques - vital for the understanding and development of new technologies Written and edited by leading experts in the field, with contributors belonging to the European Commission's FP7 Network of Excellence NEWCOM++ Applications to a wide range of fields, including sensor networks, emergency services, military use, location-based billing, location-based advertising, intelligent transportation, and leisure Location-aware personal devices and location-based services have become ever more prominent in the past few years, thanks to the significant advances in position location technology. Sensor networks, geographic information, emergency services, location management, location-based billing, location-based advertising, intelligent transportation, and leisure applications are just some of the potential applications that can be enabled by these techniques. Increasingly, satellite and terrestrial positioning techniques are being combined for maximum performance; to produce the next wave of location-based devices and services, engineers need to combine both components. This book is the first to present a holistic view, covering all aspects of positioning: both terrestrial and satellite, both theory and practice, both performance bounds and signal processing techniques. It will provide a valuable resource for product developers and R&D engineers, allowing them to improve existing location techniques and develop future approaches for new systems.

The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.

RFID and Wireless Sensors using Ultra-Wideband Technology explores how RFID-based technologies are becoming the first choice to realize the last (wireless) link in the chain between each element and the Internet due to their low cost and simplicity. Each day, more and more elements are being connected to the Internet of Things. In this book, ultra-wideband radio technology (in time domain) is exploited to realize this wireless link. Chipless, semi-passive and active RFID systems and wireless sensors and prototypes are proposed in terms of reader (setup and signal processing techniques) and tags (design, integration of sensors and performance). The authors include comprehensive theories, proposals of advanced techniques, and their implementation to help readers develop time-domain ultra-wideband radio technology for a variety of applications. This book is suitable for post-doctoral candidates, experienced researchers, and engineers developing RFID, tag antenna designs, chipless RFID, and sensor integration.

This book describes the signal, image and video processing methods and techniques for fire detection and provides a thorough and practical overview of this important subject, as a number of new methods are emerging. This book will serve as a reference for signal processing and computer vision, focusing on fire detection and methods for volume sensors. Applications covered in this book can easily be adapted to other domains, such as multi-modal object recognition in other safety and security problems, with scientific importance for fire detection, as well as video surveillance. Coverage includes: Camera Based Techniques Multi-modal/Multi-sensor fire analysis Pyro-electric Infrared Sensors for Flame Detection Large scale fire experiments Wildfire detection from moving aerial platforms

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm Unsupervised deep learning Machine vision and image retrieval

The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.

Speech enhancement is a classical problem in signal processing, yet still largely unsolved. Two of the conventional approaches for solving this problem are linear filtering, like the classical Wiener filter, and subspace methods. These approaches have traditionally been treated as different classes of methods and have been introduced in somewhat different contexts. Linear filtering methods originate in stochastic processes, while subspace methods have largely been based on developments in numerical linear algebra and matrix approximation theory.

This book bridges the gap between these two classes of methods by showing how the ideas behind subspace methods can be incorporated into traditional linear filtering. In the context of subspace methods, the enhancement problem can then be seen as a classical linear filter design problem. This means that various solutions can more easily be compared and their performance bounded and assessed in terms of noise reduction and speech distortion. The book shows how various filter designs can be obtained in this framework, including the maximum SNR, Wiener, LCMV, and MVDR filters, and how these can be applied in various contexts, like in single-channel and multichannel speech enhancement, and in both the time and frequency domains.

Human hands are natural tools for performing actions and gestures that interact with the physical world. Radar technology allows for touchless wireless gesture sensing by transmitting radio frequency (RF) signals to the target, analyzing the backscattering reflections to extract the target's movements, and thereby accurately detecting gestures for Human Computer Interaction (HCI). A key advantage of this technology is that it allows interaction with machines without any need to attach a sensing device to the hands. Led by researchers from Google's Project Soli, the authors introduce the concept and underpinning technology, cover all design phases, and provide researchers and professionals with the latest advances and innovations in microwave and millimeter wave radar sensing to capture relative movements such as micro gestures.

This book gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms.

This book also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams.

New to this edition:

New appendices on random processes, information theory

New coverage of image analysis - edge detection, linking, clustering, and segmentation

Expanded coverage on image sensing and perception, including color spaces.

Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC.

Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding.

More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming.

New coverage of super-resolution methods for image and video.
Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected.
New chapters on introductory random processes, information theory, and image enhancement and analysis
Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC)

This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems.
Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience.
A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing communityContains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience researchPresents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems

DSP is utilized in just about every electronic system or device. DSP is taking one piece of information be it data, image, video, or audio, most likely compressing, sending, and filtering it to another location within your application to appear in the form of a document, picture or video.

Like Smith before it, this book is different to most on the market by following a popular applied approach to this tricky subject, and will be the perfect starting point for engineers who need to get into DSP from the ground floor. This book starts with the absolute basics of this integral process.

No experience is expected and with no prior knowledge taken for granted, a refresher chapter on complex numbers and trigonometry can be found at the very beginning of the material. Real-world worked examples, reference designs, and tools - including online applets that enable readers to visualize key principles - complete a package that will help engineers who that needs to learn anew or refresh their memory on this essential technology as they move to projects that require DSP familiarity.
Dismayed when presented with a mass of equations as an explanation of DSP? This is the book for you

Clear examples and a non-mathematical approach gets you up to speed with DSP

Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems

This book provides a full representation of Inverse Synthetic Aperture Radar (ISAR) imagery, which is a popular and important radar signal processing tool. The book covers all possible aspects of ISAR imaging. The book offers a fair amount of signal processing techniques and radar basics before introducing the inverse problem of ISAR and the forward problem of Synthetic Aperture Radar (SAR). Important concepts of SAR such as resolution, pulse compression and image formation are given together with associated MATLAB codes.

After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLAB codes and figures are included. The final chapter considers advanced concepts and trends in ISAR imaging.

All the design and development inspiration and direction an digital engineer needs in one blockbuster book! Kenton Williston, author, columnist, and editor of DSP DesignLine has selected the very best digital signal processing design material from the Newnes portfolio and has compiled it into this volume. The result is a book covering the gamut of DSP design?from design fundamentals to optimized multimedia techniques?with a strong pragmatic emphasis. In addition to specific design techniques and practices, this book also discusses various approaches to solving DSP design problems and how to successfully apply theory to actual design tasks. The material has been selected for its timelessness as well as for its relevance to contemporary embedded design issues.
CONTENTS:
Chapter 1 ADCs, DACs, and Sampling Theory
Chapter 2 Digital Filters
Chapter 3 Frequency Domain Processing
Chapter 4 Audio Coding
Chapter 5 Video Processing
Chapter 6 Modulation
Chapter 7 DSP Hardware Options
Chapter 8 DSP Processors and Fixed-Point Arithmetic
Chapter 9 Code Optimization and Resource Partitioning
Chapter 10 Testing and Debugging DSP Systems
*Hand-picked content selected by Kenton Williston, Editor of DSP DesignLine
*Proven best design practices for image, audio, and video processing
*Case histories and design examples get you off and running on your current project

Digital signal processing is commonplace in most electronics including MP3 players, HDTVs, and phones, just to name a few of the applications. The engineers creating these devices are in need of essential information at a moment's notice. The Instant Access Series provides all the critical content that a signal or communications engineer needs in his or her daily work.
This book provides an introduction to DSPs as well as succinct overviews of linear systems, digital filters, and digital compression. This book is filled with images, figures, tables, and easy to find tips and tricks for the engineer that needs material fast to complete projects to deadline.

*Tips and tricks feature that will help engineers get info fast and move on to the next issue
*Easily searchable content complete with tabs, chapter table of contents, bulleted lists, and boxed features
*Just the essentials, no need to page through material not needed for the current project

This book treats essentials from neurophysiology (Hodgkin-Huxley equations, synaptic transmission, prototype networks of neurons) and related mathematical concepts (dimensionality reductions, equilibria, bifurcations, limit cycles and phase plane analysis). This is subsequently applied in a clinical context, focusing on EEG generation, ischaemia, epilepsy and neurostimulation. The book is based on a graduate course taught by clinicians and mathematicians at the Institute of Technical Medicine at the University of Twente. Throughout the text, the author presents examples of neurological disorders in relation to applied mathematics to assist in disclosing various fundamental properties of the clinical reality at hand. Exercises are provided at the end of each chapter; answers are included. Basic knowledge of calculus, linear algebra, differential equations and familiarity with MATLAB or Python is assumed. Also, students should have some understanding of essentials of (clinical) neurophysiology, although most concepts are summarized in the first chapters. The audience includes advanced undergraduate or graduate students in Biomedical Engineering, Technical Medicine and Biology. Applied mathematicians may find pleasure in learning about the neurophysiology and clinic essentials applications. In addition, clinicians with an interest in dynamics of neural networks may find this book useful, too.