This book collects a wealth of information about spatial audio coding into one comprehensible volume. It is a thorough reference to the 3GPP and MPEG Parametric Stereo standards and the MPEG Surround multi-channel audio coding standard. It describes key developments in coding techniques, which is an important factor in the optimization of advanced entertainment, communications and signal processing applications. Until recently, technologies for coding audio signals, such as redundancy reduction and sophisticated source and receiver models did not incorporate spatial characteristics of source and receiving ends. Spatial audio coding achieves much higher compression ratios than conventional coders. It does this by representing multi-channel audio signals as a downmix signal plus side information that describes the perceptually-relevant spatial information. Written by experts in spatial audio coding, Spatial Audio Processing: reviews psychoacoustics (the relationship between physical measures of sound and the corresponding percepts) and spatial audio sound formats and reproduction systems; brings together the processing, acquisition, mixing, playback, and perception of spatial audio, with the latest coding techniques; analyses algorithms for the efficient manipulation of multiple, discrete and combined spatial audio channels, including both MP3 and MPEG Surround; shows how the same insights on source and receiver models can also be applied for manipulation of audio signals, such as the synthesis of virtual auditory scenes employing head-related transfer function (HRTF) processing and stereo to N-channel audio upmix. Audio processing research engineers and audio coding research and implementation engineers will find this an insightful guide. Academic audio and psychoacoustic researchers, including post-graduate and third/fourth year students taking courses in signal processing, audio and speech processing, and telecommunications, will also benefit from the information inside.
Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference.
The arrival, and continuing evolution, of high quality 3D objects has been made possible by recent progress in 3D scanner acquisition and 3D graphics rendering. With this increasing quality comes a corresponding increase in the size and complexity of the data files and the necessity for advances in compression techniques. Effective indexing to facilitate the retrieval of the 3D data is then required to efficiently store, search and recapture the objects that have been compressed. The application of 3D images in fields such as communications, medicine and the military also calls for copyright protection, or watermarking, to secure the data for transmission. Written by expert contributors, this timely text brings together the three important and complementary topics of compression, retrieval and watermarking techniques for 3D objects. 3D object processing applications are developing rapidly and this book tackles the challenges and opportunities presented, focusing on the secure transmission, sharing and searching of 3D objects on networks, and includes: an introduction to the commonly used 3D representation schemes; the characteristics, advantages and limitations of polygonal meshes, surface based models and volumetric models; 3D compression techniques; the 3D coding and decoding schemes for reducing the size of 3D data to reduce transmission time and minimize distortion; state of the art responses to the intrinsic challenges of building a 3D-model search engine, considering view-based, structural and full-3D approaches; watermarking techniques for ensuring intellectual property protection and content security without altering the visual quality of the 3D object. 3D Object Processing: Compression, Indexing and Watermarking is an invaluable resource for graduate students and researchers working in signal and image processing, computer aided design, animation and imaging systems. Practising engineers who want to expand their knowledge of 3D video objects, including data compression, indexing, security, and copyrighting of information, will also find this book of great use.
This book describes in a comprehensive manner the components and systems of fiber optic communications and networks. The first section explains the theory of multimode and single-mode fibers, then the technological features, including manufacturing, cabling, and connecting. The second section describes the various components (passive and active optical components, integrated optics, opto-electronic transmitters and receivers, and optical amplifiers) used in fiber optic systems. Finally, the optical transmission system design is explained, and applications to optical networks and fiber optic sensors are detailed, including the most recent developments in switched networks, high bit-rate systems, and FTTH or radio over fiber.
Fiber Optic Essentials starts with a basic discussion on lightwaves and the phenomenon of refraction and reflection. It then goes on to introduces the reader to the field of fiber optics and covers some of the recent developments, such as fiber amplifiers, dispersion compensation and nonlinear effects. A number of other applications are also presented. Examples and comparison with everyday experience are provided wherever possible to help the reader's comprehension. Diagrams are also included to aid in the visualization of certain concepts.
Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.
The recent evolution of digital technology has resulted in the design of digital processors with increasingly complex capabilities. The implementation of hardware/software co-design methodologies provides new opportunities for the development of low power, high speed DSPs and processor networks. Dedicated digital processors are digital processors with an application specific computational task. Dedicated Digital Processors presents an integrated and accessible approach to digital processor design principles, processes, and implementations based upon the author's considerable experience in teaching digital systems design and digital signal processing. Emphasis is placed on presentation of hardware/software co-design methods, with examples and illustrations provided throughout the text. System-on-a-chip and embedded systems are described and examples of high speed real-time processing are given. Coverage of standard and emerging DSP architectures enable the reader to make an informed selection when undertaking their own designs. Presents readers with the elementary building blocks for the design of digital hardware systems and processor networks Provides a unique evaluation of standard DSP architectures whilst providing up-to-date information on the latest architectures, including the TI 55x and TigerSharc chip families and the Virtex FPGA (field-programmable gate array) Introduces the concepts and methodologies for describing and designing hardware VHDL is presented and used to illustrate the design of a simple processor A practical overview of hardware/software codesign with design techniques and considerations illustrated with examples of real-world designs Fundamental reading for graduate and senior undergraduate students of computer and electronic engineering, and Practicing engineers developing DSP applications.
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.
Digital signal processing is essential for improving the accuracy and reliability of a range of engineering systems, including communications, networking, and audio and video applications. Using a combination of programming and mathematical techniques, it clarifies, or standardizes the levels or states of a signal, in order to meet the demands of designing high performance digital hardware. Written by authors with a wealth of practical experience working with digital signal processing, this text is an excellent step-by-step guide for practitioners and researchers needing to understand and quickly implement the technology. Split into six, self-contained chapters, Digital Signal Processing: A Practitioner’s Approach covers: basic principles of signal processing such as linearity, stability, convolution, time and frequency domains, and noise; descriptions of digital filters and their realization, including fixed point implementation, pipelining, and field programmable gate array (FGPA) implementation; Fourier transforms, especially discrete (DFT), and fast Fourier transforms (FFT); case studies demonstrating difference equations, direction of arrival (DoA), and electronic rotating elements, and MATLAB programs to accompany each chapter. A valuable reference for engineers developing digital signal processing applications, this book is also a useful resource for electrical and computer engineering graduates taking courses in signal processing.
The enormous advances in digital signal processing (DSP) technology have contributed to the wide dissemination and success of speech communication devices – be it GSM and UMTS mobile telephones, digital hearing aids, or human-machine interfaces. Digital speech transmission techniques play an important role in these applications, all the more because high quality speech transmission remains essential in all current and next generation communication networks. Enhancement, coding and error concealment techniques improve the transmitted speech signal at all stages of the transmission chain, from the acoustic front-end to the sound reproduction at the receiver. Advanced speech processing algorithms help to mitigate a number of physical and technological limitations such as background noise, bandwidth restrictions, shortage of radio frequencies, and transmission errors. Digital Speech Transmission provides a single-source, comprehensive guide to the fundamental issues, algorithms, standards, and trends in speech signal processing and speech communication technology. The authors give a solid, accessible overview of fundamentals of speech signal processing speech coding, including new speech coders for GSM and UMTS error concealment by soft decoding artificial bandwidth extension of speech signals single and multi-channel noise reduction acoustic echo cancellation This text is an invaluable resource for engineers, researchers, academics, and graduate students in the areas of communications, electrical engineering, and information technology.