Drawing from physics and philosophical debates, Ismael combines a set of essays on the time worn debate of symmetry from both fields.

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.

This proceedings book presents the latest research in the fields of information theory, communication system, computer science and signal processing, as well as other related technologies. Collecting selected papers from the 3rd Conference on Signal and Information Processing, Networking and Computers (ICSINC), held in Chongqing, China on September 13-15, 2017, it is of interest to professionals from academia and industry alike.

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.

Signal Processing: A Mathematical Approach 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. Assuming an advanced undergraduate- or graduate-level understanding of mathematics-including familiarity with Fourier series, matrices, probability, and statistics-this Second Edition: Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filters Expands the material on Fourier analysis to three new chapters to provide additional background information Presents real-world examples of applications that demonstrate how mathematics is used in remote sensing Featuring problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.

The introduction and preliminary chapters discuss the background and development of CCD technology, and the structure and operation of CCD image sensors. Subsequent chapters examine the technology and sensor manufacturing process, including modelling, the theories behind digital imaging processing, and the applications of digital cameras. Finally, the editor discusses future technological and market trends anticipated in this fast growing industry.
This title contains the most up-to-date and comprehensive information on the development of the Charge-Coupled Device (CCD), which makes possible the widespread use of consumer camcorders and broadcasting color cameras. The material in this book is comprehensive enough to be of great value to researchers, industrialists and post-graduate students in the area of image technology, while the simplicity and clarity of explanation make it easy to understand to the non-expert.

An essential task in radar systems is to find an appropriate solution to the problems related to robust signal processing and the definition of signal parameters. Signal Processing in Radar Systems addresses robust signal processing problems in complex radar systems and digital signal processing subsystems. It also tackles the important issue of defining signal parameters. The book presents problems related to traditional methods of synthesis and analysis of the main digital signal processing operations. It also examines problems related to modern methods of robust signal processing in noise, with a focus on the generalized approach to signal processing in noise under coherent filtering. In addition, the book puts forth a new problem statement and new methods to solve problems of adaptation and control by functioning processes. Taking a systems approach to designing complex radar systems, it offers readers guidance in solving optimization problems. Organized into three parts, the book first discusses the main design principles of the modern robust digital signal processing algorithms used in complex radar systems. The second part covers the main principles of computer system design for these algorithms and provides real-world examples of systems. The third part deals with experimental measurements of the main statistical parameters of stochastic processes. It also defines their estimations for robust signal processing in complex radar systems. Written by an internationally recognized professor and expert in signal processing, this book summarizes investigations carried out over the past 30 years. It supplies practitioners, researchers, and students with general principles for designing the robust digital signal processing algorithms employed by complex radar systems.

Multiculturalism and diversity have raised a number of challenges for liberal democracy, not least the stigmatization of people in response to these developments. In this book, leading experts from a range of disciplines look at the responses to stigmatization from the perspectives of ordinary people. They use a range of case studies drawn from the US, Brazil, Canada, France, Israel, South Africa, and Sweden: the first systematic qualitative and cross-national exploration of how diverse minority groups respond to stigmatization in the course of their everyday lives. The chapters in this book tackle a range of theoretical questions about stigmatization, including how they make sense of their experiences, how they shape subsequent behaviour, and how they negotiate and transform social and symbolic boundaries within a range of social and institutional contexts. Responses to Stigmatization in Comparative Perspective provides new data and analysis of how stigmatization affects a range of societies, and its original research and analysis will be important reading for those studying Ethnicity, as well as Sociologists, Political Scientists, and Anthropologists. This book was originally published as a special issue of Ethnic and Racial Studies.

Nonlinear Optical Systems: Principles, Phenomena, and Advanced Signal Processing is a simplified overview of the evolution of technology associated with nonlinear systems and advanced signal processing. This book's coverage ranges from fundamentals to phenomena to the most cutting-edge aspects of systems for next-generation biomedical monitoring and nonlinear optical transmission.

The authors address how these systems are applied through photonic signal processing in contemporary optical systems for communications and/or laser systems. They include a concise but sufficient explanation of mathematical representation of nonlinear equations to provide insight into nonlinear dynamics at different phases. The book also describes advanced aspects of solitons and bound solitons for passive- and active-mode locked fiber lasers, in which higher-order differential equations can be employed to represent the dynamics of amplitude evolution in the current or voltages of lightwaves in such systems.

Covering a wide range of topics, this book:

• Introduces nonlinear systems and some mathematical representations, particularly the routes to chaos and bifurcation
• Describes nonlinear fiber lightwave lasing systems
• Covers nonlinear phenomena in fiber lasers, including both passive and active energy storage cavities
• Experimentally and theoretically demonstrates soliton pulses, in which lightwaves are the carrier under their envelopes
• Assembles and demonstrates sequences of both single and multiple solitons in a group and then assesses their dynamics in detail
• Examines the evolution of bound solitons, which are transmitted through single-mode optical fibers that compose a phase variation system

This text outlines the theory and techniques used in nonlinear physics and applications for physical systems. It also illustrates the use of MATLAB(r) and Simulink(r) computer models and processing techniques for nonlinear signals. Building on readers' newly acquired fundamental understanding of nonlinear systems and associated signal processing, the book then demonstrates the use of such applications in real-world, practical environments.

Signal Processing for Intelligent Sensors with MATLAB (R), Second Edition once again presents the key topics and salient information required for sensor design and application. Organized to make it accessible to engineers in school as well as those practicing in the field, this reference explores a broad array of subjects and is divided into sections: Fundamentals of Digital Signal Processing, Frequency Domain Processing, Adaptive System Identification and Filtering, Wavenumber Sensor Systems, and Signal Processing Applications. Taking an informal, application-based approach and using a tone that is more engineer-to-engineer than professor-to-student, this revamped second edition enhances many of the features that made the original so popular. This includes retention of key algorithms and development methodologies and applications, which are creatively grouped in a way that differs from most comparable texts, to optimize their use. New for the Second Edition: Inclusion of more solved problems Web access to a large collection of MATLAB (R) scripts used to support data graphs presented throughout the book Additional coverage of more audio engineering, transducers, and sensor networking technology A new chapter on Digital Audio processing reflects a growing interest in digital surround sound (5.1 audio) techniques for entertainment, home theaters, and virtual reality systems New sections on sensor networking, use of meta-data architectures using XML, and agent-based automated data mining and control Serving dual roles as both a learning resource and a field reference on sensor system networks, this book progressively reveals digestible nuggets of critical information to help readers quickly master presented algorithms and adapt them to meet their requirements. It illustrates the current trend toward agile development of web services for wide area sensor networking and intelligent processing in the sensor system networks that are employed in homeland security, business, and environmental and demographic information systems.

A proven, cost-effective approach to solving analog signal processing design problems

Most design problems involving analog circuits require a great deal of creativity to solve. But, as the authors of this groundbreaking guide demonstrate, finding solutions to most analog signal processing problems does not have to be that difficult.

Analog Signal Processing presents an original, five-step, design-oriented approach to solving analog signal processing problems using standard ICs as building blocks. Unlike most authors who prescribe a "bottom-up" approach, Professors Pallás-Areny and Webster cast design problems first in functional terms and then develop possible solutions using available ICs, focusing on circuit performance rather than internal structure. The five steps of their approach move from signal classification, definition of desired functions, and description of analog domain conversions to error classification and error analysis.

Featuring 90 worked examples—many of them drawn from actual implementations—and more than 130 skill-building chapter-end problems, Analog Signal Processing is both a valuable working resource for practicing design engineers and a textbook for advanced courses in electronic instrumentation design.

Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today's powerful computing capabilities, they can be used in a wide range of application areas, including engineering, communications, geophysics, computer science, information technology, medicine, and biometrics. Updated and expanded, Digital Signal Processing with Examples in MATLAB (R), Second Edition introduces the basic aspects of signal processing and presents the fundamentals of DSP. It also relates DSP to continuous signal processing, rather than treating it as an isolated operation. New to the Second Edition Discussion of current DSP applications New chapters on analog systems models and pattern recognition using support vector machines New sections on the chirp z-transform, resampling, waveform reconstruction, discrete sine transform, and logarithmic and nonuniform sampling A more comprehensive table of transforms Developing the fundamentals of DSP from the ground up, this bestselling text continues to provide readers with a solid foundation for further work in most areas of signal processing. For novices, the authors review the basic mathematics required to understand DSP systems and offer a brief introduction to MATLAB. They also include end-of-chapter exercises that not only provide examples of the topics discussed, but also introduce topics and applications not covered in the chapters.

The second, strongly enlarged edition of the textbook gives a substantial insight into the characteristics and the design of digital filters. It briefly introduces to the theory of continuous-time systems and the design methods for analog filters. Time-discrete systems, the basic structures of digital filters, sampling theorem, and the design of IIR filters are widely discussed. The author devotes important parts to the design of non-recursive filters and the effects of finite register length. The explanation of techniques like oversampling and noise shaping conclude the book. The author has substantially updated all chapters and added some important topics like Allpass filters. With an emphasize put on the practical implementation of theoretical concepts, the book is a reference for advanced students as well as practicing engineers.

The most outstanding feature of this book is that it treats the design of filters that approximate a constant group delay, and both, the prescribed magnitude and group delay response of one-dimensional as well as two-dimensional digital filters. It so fills a void in the literature, that almost solely deals with the magnitude response of the filter transfer function. The volume contains many of the important results that have appeared in professional journals only recently.

This book offers an introduction to digital signal processing (DSP) with an emphasis on audio signals and computer music. It covers the mathematical foundations of DSP, important DSP theories including sampling, LTI systems, the z-transform, FIR/IIR filters, classic sound synthesis algorithms, various digital effects, topics in time and frequency-domain analysis/synthesis, and associated musical/sound examples. Whenever possible, pictures and graphics are included when presenting DSP concepts of various abstractions. To further facilitate understanding of ideas, a plethora of MATLAB (R) code examples are provided, allowing the reader tangible means to "connect dots" via mathematics, visuals, as well as aural feedback through synthesis and modulation of sound. This book is designed for both technically and musically inclined readers alike-folks with a common goal of exploring digital signal processing.

Developing algorithms for multi-dimensional Fourier transforms, this book presents results that yield highly efficient code on a variety of vector and parallel computers. By emphasising the unified basis for the many approaches to both one-dimensional and multidimensional Fourier transforms, this book not only clarifies the fundamental similarities, but also shows how to exploit the differences in optimising implementations. It will thus be of great interest not only to applied mathematicians and computer scientists, but also to seismologists, high-energy physicists, crystallographers, and electrical engineers working on signal and image processing.

Signal Analysis explores methods that offer an insight into the properties of signals and stochastic processes. This comprehensive and authoritative book provides an introduction to the fundamental theory of signal analysis. It bridges the gap between the basic knowledge in system theory and the specialist knowledge in various fields of signal processing and provides a complete overview of current applications. Features include:

• Focus on both classical and modern approaches to transforms, such as the Karhunen—Loève transform and the discrete Fourier transform
• Enhancement of the understanding and relation of transform theory
• Discussion of recent and emerging topics, including filter banks with perfect reconstruction time-frequency and wavelets.

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 first volume, Foundations, introduces core topics in inference and learning, such as matrix theory, linear algebra, random variables, convex optimization and stochastic optimization, and prepares students for studying their practical application in later volumes. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 600 end-of-chapter problems (including solutions for instructors), 100 figures, 180 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Inference 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.

Classical signal processing techniques are based primarily on the analog nature of all signals. However, the continuously improving performance of digital circuitry and processors has prompted a switch to digital signal processing techniques rather than the traditional analog ones.

Applied Signal Processing recognizes the linkage between the two paradigms and presents a unified treatment of both subjects (analog and digital signal processing) in one authoritative volume. It introduces underlying principles, basic concepts, and definitions as well as classic and contemporary designs of signal processing systems. The author includes a detailed description of data converters, an interface between the real world of analog signals and the artificial world of digital signals. He provides a concise presentation of topics by limiting the number of complex equations and using lucid language. Numerous real-world application examples are featured within each chapter including architectures from Texas Instruments, Motorola, and Analog Devices.

With its compounded coverage of both analog and digital signal processing techniques, this book provides engineers with the knowledge they need to understand the analog basis of modern digital signal processing techniques and construct architectures for modern systems.

Designed to cover the fundamental concepts of digital signal processing, the book introduces topics such as discrete-time signals, the z-transform, frequency analysis, discrete and fast Fourier transforms, digital filters, FIR, statistical DSP, applications, and more. DSP has been applied in most disciplines ranging from engineering to telecommunications, and from astronomy to medical imaging. This book focuses on the fundamentals of DSP, namely on the representation of signals by mathematical models and on the processing of signals by discrete-time systems. Features Designed to cover the fundamental concepts of DSP Introduces topics such as discrete-time signals, the z-transform, frequency analysis, discrete and fast Fourier transforms, digital filters, FIR, statistical DSP, applications, and more Features a variety of exercises and a glossary

World-class experts from academia and industry assembled at the sixth Biennial Workshop on Digital Signal Processing (DSP) for In-Vehicle Systems at Korea University, Seoul, Korea in 2013. The Workshop covered a wide spectrum of automotive fields, including in-vehicle signal processing and cutting-edge studies on safety, driver behavior, infrastructure, in-vehicle technologies. Contributors to this volume have expanded their contributions to the Workshop into full chapters with related works, methodology, experiments, and the analysis of the findings. Topics in this volume include: DSP technologies for in-vehicle systems Driver status and behavior monitoring In-Vehicle dialogue systems and human machine interfaces In-vehicle video and applications for safety Passive and active driver assistance technologies Ideas and systems for autonomous driving Transportation infrastructure

The problem of noise immunity is a key problem for complex signal processing systems research in science and engineering. New approaches to such problems allow the development of a better quality of signal detection in noise.

This book is devoted to a new generalized approach to signal detection theory. The main purpose is to present the basic fundamental concepts of the generalized approach to signal processing in noise and to show how it may be applied in various areas of signal processing. The generalized approach allows extension of the well-known boundaries of the potential noise immunity set up by classical and modern signal detection theories. New approaches for construction of detectors with the amplitude, frequency, and phase tracking systems based on the generalized approach are presented.

Features and Topics:

* New approaches to the statistical theory of signal detection

* New features of signal detection based on experimental study

* More rigorous definition of potential noise immunity

* Chapter summaries and an analsys of recent observations obtained by computer modeling and experiment

* Particularly useful applications for detection problems in radar, communications, wireless communications, acoustics, remote sensing, sonar, underwater signal processing, geophysical signal processing, and biomedical signal processing.

The book is an excellent resource for understanding and solving problems in modern signal detection theories. Professionals, scientists, engineers, and researchers in electrical engineering, computer science, geophysics, and applied mathematics will benefit from using the techniques presented.

The First International Conference on Signal and Information Processing, Networking and Computers (ICSINC) focuses on the key technologies and challenges of signal and information processing schemes, network application, computer theory and application, etc. Topics in this conference include: Information TheoryThe work contains state-of-the-art research work in the field of information theory from traditional media coding theory, compressing and streaming theory to the latest quantum theory & statistics and big data analytics, featuring the most active research interests in this field. Communication SystemAs a traditional and fundamental aspect of the conference in the field of signal processing and networking, ICSINC publications includes research works focusing on physical layer transmission theory such as MIMO transmission, adaptive antenna theory, and radar and satellite transmission, etc. Research works in the field of SDN, wireless security and 5G related theories are also included. Computer ScienceThe conference also encompasses relevant topics in computer science such as AI & neural network, patter recognition & learning, and medical image processing etc. Other topics such as internet application, biometric & authentication are also included. WorkshopICSINC features workshops hosted by experts from the industrial world. The workshop on Telecom Big Data based Research and Application promotes the in-depth exploration of the most recent research and development findings on the basis of telecom big data. This workshop provides participation of the industry to showcase and commercialize their relevant technology and application as well as products. All materials will be included in publication.

This book describes a completely novel mathematical development which has already influenced probability theory, and has potential for application to engineering and to areas of pure mathematics.

Spreadin' Rhythm Around: Black Popular Songwriters,1880-1930 is a classic work on a little-studied subject in American music history: the contribution of African-American songwriters to the world of popular song. Hailed by Publishers Weekly as "thoroughly researched and entertainingly written," this work documents the careers of songwriters like James A. Bland ("Carry Me Back to Ole Virginny"), Bert Williams ("Nobody"), W. C. Handy ("St. Louis Blues"), Noble Sissle, Eubie Blake ("I'm Just Wild About Harry"), and many more. Richly illustrated with rare photographs from sheet music, newspapers, and other unique sources, the book documents an entire era of performance when black singers, dancers, and actors were active on the New York stage. In sheer depth of research, new information, and full coverage, Spreadin' Rhythm Around offers a comprehensive picture of the contributions of black musicians to American popular song. For anyone interested in the history of jazz, pop song, or Broadway, this book will be a revelation.