In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal’s pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users. Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications, Pseudo Random Signal Processing: Theory and Application: sets out the mathematical foundations needed to implement powerful pseudo random signal processing techniques; presents information about binary and nonbinary pseudo random sequence generation and design objectives; examines the creation of system architectures, including those with microprocessors, digital signal processors, memory circuits and software suits; gives a detailed discussion of sophisticated applications such as spread spectrum communications, ranging and satellite navigation systems, scrambling, system verification, and sensor and optical fibre systems. Pseudo Random Signal Processing: Theory and Applicationis an essential introduction to the subject for practising Electronics Engineers and researchers in the fields of mobile communications, satellite navigation, signal analysis, circuit testing, cryptology, watermarking, and measurement. It is also a useful reference for graduate students taking courses in Electronics, Communications and Computer Engineering.

Multimedia Signal Processing is a comprehensive and accessible text to the theory and applications of digital signal processing (DSP). The applications of DSP are pervasive and include multimedia systems, cellular communication, adaptive network management, radar, pattern recognition, medical signal processing, financial data forecasting, artificial intelligence, decision making, control systems and search engines. This book is organised in to three major parts making it a coherent and structured presentation of the theory and applications of digital signal processing. A range of important topics are covered in basic signal processing, model-based statistical signal processing and their applications. Part 1: Basic Digital Signal Processing gives an introduction to the topic, discussing sampling and quantization, Fourier analysis and synthesis, Z-transform, and digital filters. Part 2: Model-based Signal Processing covers probability and information models, Bayesian inference, Wiener filter, adaptive filters, linear prediction hidden Markov models and independent component analysis. Part 3: Applications of Signal Processing in Speech, Music and Telecommunications explains the topics of speech and music processing, echo cancellation, deconvolution and channel equalization, and mobile communication signal processing. Covers music signal processing, explains the anatomy and psychoacoustics of hearing and the design of MP3 music coder Examines speech processing technology including speech models, speech coding for mobile phones and speech recognition Covers single-input and multiple-inputs denoising methods, bandwidth extension and the recovery of lost speech packets in applications such as voice over IP (VoIP) Illustrated throughout, including numerous solved problems, Matlab experiments and demonstrations Companion website features Matlab and C++ programs with electronic copies of all figures. This book is ideal for researchers, postgraduates and senior undergraduates in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be a valuable text to professional engineers in telecommunications and audio and signal processing industries.

This book brings together papers presented at the 2017 International Conference on Communications, Signal Processing, and Systems (ICCSP 2017), which was held on July 14–17, 2017 in Harbin, China. Presenting the latest developments and discussing the interactions and links between these multidisciplinary fields, the book spans topics ranging from communications, signal processing and systems. It is aimed at undergraduate and graduate electrical engineering, computer science and mathematics students, researchers and engineers from academia and industry as well as government employees.

As demand for applications working in extended frequency ranges increases, classical Digital signal processing (DSP) techniques, not protected against aliasing, are becoming less effective. Digital alias-free signal processing (DASP) is a technique for overcoming the problems of aliasing at extended frequency ranges. Based on non-uniform or randomised sampling techniques and the development of novel algorithms, it creates the capacity to suppress potential aliasing crucial for high frequency applications and to reduce the complexity of designs. This book provides practical and comprehensive coverage of the theory and techniques behind alias-free digital signal processing. Key features: Analyses issues of sampling, randomised and pseudo-randomised quantisation and direct and indirectly randomised sampling. Examines periodic and hybrid sampling, including information on processing algorithms and potential limitations imposed by signal dynamics. Sets out leading methods and techniques for complexity reduced designs, in particular designs of large aperture sensor arrays, massive data acquisition and compression from a number of signal sources and complexity-reduced processing of non-uniform data. Presents examples of engineering applications using these techniques including spectrum analysis, waveform reconstruction and the estimation of various parameters, emphasising the importance of the technique for developing new technologies. Links DASP and traditional technologies by mapping them into embedded systems with standard inputs and outputs. Digital Alias-free Signal Processing is ideal for practising engineers and researchers working on the development of digital signal processing applications at extended frequencies. It is also a valuable reference for electrical and computer engineering graduates taking courses in signal processing or digital signal processing.

Industrial Process Identification brings together the latest advances in perturbation signal design. It describes the approaches to the design process that are relevant to industries. The authors’ discussion of several software packages (Frequency Domain System Identification Toolbox, prs, GALOIS, multilev_new, and Input-Signal-Creator) will allow readers to understand the different designs in industries and begin designing common classes of signals. The authors include two case studies that provide a balance between the theory and practice of these designs: the identification of a direction-dependent electronic nose system; and the identification of a multivariable cooling system with time-varying delay. Major aspects of signal design such as the formulation of suitable specifications in the face of practical constraints, the classes of designs available, the various objectives necessitating separate treatments when dealing with nonlinear systems, and extension to multi-input scenarios, are discussed. Codes, including some that will produce simulated data, are included to help readers replicate the results described. Industrial Process Identification is a powerful source of information for control engineers working in the process and communications industries seeking guidance on choosing identification software tools for use in practical experiments and case studies. The book will also be of interest to academic researchers and students working in electrical, mechanical and communications engineering and the application of perturbation signal design. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.