Advanced Signal Processing

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Advanced Signal Processing

Author : D. J. Creasey
ISBN : 0863410375
Genre : Technology & Engineering
File Size : 67.64 MB
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Covers the many aspects of modern signal processing systems from the transduction unit through to the display. Contents include: Transmitter aerials. High power amplifier design for active sonar. Radar transmitters. Receiver array technology for sonar. New underwater acoustic sensors. GaAs IC amplifiers for radar and communication receivers. Integrated optical techniques for acousto-optic receivers. Logarithmic receivers. CCD processors for sonar. Very high speed integrated circuits (VHSIC) technology for digital signal processing applications. Digital filters. Display types. Scan converters in sonar. Display ergonomics. High throughput sonar processors. Optical fibre systems for signal processing. Satellite communications.
Category: Technology & Engineering

Advanced Signal Processing For Communication Systems

Author : Tadeusz Wysocki
ISBN : 9780306477911
Genre : Science
File Size : 31.53 MB
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Advanced Signal Processing for Communication Systems consists of 20 contributions from researchers and experts. The first group of chapters deals with the audio and video processing for communications applications, including topics ranging from multimedia content delivery over the Internet, through the speech processing and recognition to recognition of non-speech sounds that can be attributed to the surrounding environment. The book also includes sections on applications of error control coding, information theory, and digital signal processing for communication systems like modulation, software-defined radio, and channel estimation. Advanced Signal Processing for Communication Systems is written for researchers working on communication systems and signal processing, as well as telecommunications industry professionals.
Category: Science

Advanced Signal Processing A Concise Guide

Author : Amir-Homayoon Najmi
ISBN : 9781260458947
Genre : Technology & Engineering
File Size : 37.40 MB
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Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A comprehensive introduction to the mathematical principles and algorithms in statistical signal processing and modern neural networks. This text is an expanded version of a graduate course on advanced signal processing at the Johns Hopkins University Whiting school program for professionals with students from electrical engineering, physics, computer and data science, and mathematics backgrounds. It covers the theory underlying applications in statistical signal processing including spectral estimation, linear prediction, adaptive filters, and optimal processing of uniform spatial arrays. Unique among books on the subject, it also includes a comprehensive introduction to modern neural networks with examples in time series and image classification. Coverage includes: Mathematical structures of signal spaces and matrix factorizations linear time-invariant systems and transforms Least squares filters Random variables, estimation theory, and random processes Spectral estimation and autoregressive signal models linear prediction and adaptive filters Optimal processing of linear arrays Neural networks
Category: Technology & Engineering

Advanced Signal Processing Technology By Soft Computing

Author : Charles Hsu
ISBN : 9789810244613
Genre : Computers
File Size : 22.68 MB
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This book presents worldwide outstanding research and recent progress in the applications of neural networks, fuzzy logic, chaos, independent component analysis, etc to fields related to speech recognition enhancement, supervised Fourier demixing noise elimination, acoustic databases, the human hearing system, cancer detection, image processing, and visual communications.
Category: Computers

Advanced Signal Processing And Digital Noise Reduction

Author : Saeed V. Vaseghi
ISBN : UCSD:31822023423569
Genre : Technology & Engineering
File Size : 25.96 MB
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Bayesian Estimation and classification. Hidden markov models. Wiener filters. Kalman and adaptive least squared error filters.
Category: Technology & Engineering

Advanced Signal Processing Algorithms Architectures And Implementations Xiv

Author : Franklin T. Luk
ISBN : STANFORD:36105114971836
Genre : Technology & Engineering
File Size : 58.17 MB
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Proceedings of SPIE present the original research papers presented at SPIE conferences and other high-quality conferences in the broad-ranging fields of optics and photonics. These books provide prompt access to the latest innovations in research and technology in their respective fields. Proceedings of SPIE are among the most cited references in patent literature.
Category: Technology & Engineering

Advanced Signal Processing Handbook

Author : Stergios Stergiopoulos
ISBN : 9781351369442
Genre : Technology & Engineering
File Size : 66.21 MB
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Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems. The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes.
Category: Technology & Engineering

Lung Sounds

Author : Hadji Hadjileontiadis
ISBN : 9781598297119
Genre : Technology & Engineering
File Size : 26.76 MB
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Lung sounds auscultation is often the first noninvasive resource for detection and discrimination of respiratory pathologies available to the physician through the use of the stethoscope. Hearing interpretation, though, was the only means of appreciation of the lung sounds diagnostic information for many decades. Nevertheless, in recent years, computerized auscultation combined with signal processing techniques has boosted the diagnostic capabilities of lung sounds. The latter were traditionally analyzed and characterized by morphological changes in the time domain using statistical measures, by spectral properties in the frequency domain using simple spectral analysis, or by nonstationary properties in a joint time–frequency domain using short-time Fourier transform. Advanced signal processing techniques, however, have emerged in the last decade, broadening the perspective in lung sounds analysis. The scope of this book is to present up-to-date signal processing techniques that have been applied to the area of lung sound analysis. It starts with a description of the nature of lung sounds and continues with the introduction of new domains in their representation, new denoising techniques, and concludes with some reflective implications, both from engineers’ and physicians’ perspective. Issues of nonstationarity, nonlinearity, non-Gaussianity, modeling, and classification of lung sounds are addressed with new methodologies, revealing a more realistic approach to their pragmatic nature. Advanced denoising techniques that effectively circumvent the noise presence (e.g., heart sound interference, background noise) in lung sound recordings are described, providing the physician with high-quality auscultative data. The book offers useful information both to engineers and physicians interested in bioacoustics, clearly demonstrating the current trends in lung sound analysis. Table of Contents: The Nature of Lung Sound Signals / New Domains in LS Representation / Denoising Techniques / Reflective Implications
Category: Technology & Engineering

Advanced Signal Processing

Author : Stergios Stergiopoulos
ISBN : 9781351834933
Genre : Technology & Engineering
File Size : 80.11 MB
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Discover the Applicability, Benefits, and Potential of New Technologies As advances in algorithms and computer technology have bolstered the digital signal processing capabilities of real-time sonar, radar, and non-invasive medical diagnostics systems, cutting-edge military and defense research has established conceptual similarities in these areas. Now civilian enterprises can use government innovations to facilitate optimal functionality of complex real-time systems. Advanced Signal Processing details a cost-efficient generic processing structure that exploits these commonalities to benefit commercial applications. Learn from a Renowned Defense Scientist, Researcher, and Innovator The author preserves the mathematical focus and key information from the first edition that provided invaluable coverage of topics including adaptive systems, advanced beamformers, and volume visualization methods in medicine. Integrating the best features of non-linear and conventional algorithms and explaining their application in PC-based architectures, this text contains new data on: Advances in biometrics, image segmentation, registration, and fusion techniques for 3D/4D ultrasound, CT, and MRI Fully digital 3D/ (4D: 3D+time) ultrasound system technology, computing architecture requirements, and relevant implementation issues State-of-the-art non-invasive medical procedures, non-destructive 3D tomography imaging and biometrics, and monitoring of vital signs Cardiac motion correction in multi-slice X-ray CT imaging Space-time adaptive processing and detection of targets interference-intense backgrounds comprised of clutter and jamming With its detailed explanation of adaptive, synthetic-aperture, and fusion-processing schemes with near-instantaneous convergence in 2-D and 3-D sensors (including planar, circular, cylindrical, and spherical arrays), the quality and illustration of this text’s concepts and techniques will make it a favored reference.
Category: Technology & Engineering

Applications Of Advanced Signal Analysis

Author : Harish Parthasarathy
ISBN : 8189866850
Genre : Signal processing
File Size : 76.51 MB
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The mathematical tools used in signal analysis involve differential and difference equations, integral equations, matrix algebra and calculus, complex analysis and probability theory and random processes. This book applies these tools to problems in various branches of physics like fluid dynamics, electromagnetism and quantum theory. The book will be of use to research workers in signal processing as well as to research workers in physics and applied mathematics. Partial differential equations have been introduced here as an additional tool in signal analysis since they are used to describe quantum, electromagnetic and fluid dynamical phenomena not to forget Einstein''s equations of gravitation. The book will be of use to signal processing experts who are interested in developing tools for the analysis of signals arising in real systems
Category: Signal processing

Advanced Signal Processing On Brain Event Related Potentials

Author : Fengyu Cong
ISBN : 9789814623100
Genre : Technology & Engineering
File Size : 36.98 MB
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This book is devoted to the application of advanced signal processing on event-related potentials (ERPs) in the context of electroencephalography (EEG) for the cognitive neuroscience. ERPs are usually produced through averaging single-trials of preprocessed EEG, and then, the interpretation of underlying brain activities is based on the ordinarily averaged EEG. We find that randomly fluctuating activities and artifacts can still present in the averaged EEG data, and that constant brain activities over single trials can overlap with each other in time, frequency and spatial domains. Therefore, before interpretation, it will be beneficial to further separate the averaged EEG into individual brain activities. The book proposes systematic approaches pre-process wavelet transform (WT), independent component analysis (ICA), and nonnegative tensor factorization (NTF) to filter averaged EEG in time, frequency and space domains to sequentially and simultaneously obtain the pure ERP of interest. Software of the proposed approaches will be open-accessed. Contents:IntroductionWavelet Filter Design Based on Frequency Responses for Filtering ERP Data With Duration of One EpochIndividual-Level ICA to Extract the ERP Components from the Averaged EEG DataMulti-Domain Feature of the ERP Extracted by NTF: New Approach for Group-Level Analysis of ERPsAnalysis of Ongoing EEG by NTF During Real-World Music ExperiencesAppendix: Introduction to Basic Knowledge of Mismatch Negativity Readership: Undergraduate, graduate, researchers and professionals in the field of neurology/neuroscience, medical imaging, psychology, biomedical engineering and computer science. Key Features:Advanced signal processing approaches can be applied on averaged EEG to extract ERPs' componentsFiltering ERPs in time, frequency and space domains sequentially and simultaneouslyDemo of ERP data and MATLAB codes are open-access for the advanced signal processing approaches on ERPsKeywords:Event-Related Potentials (ERPs);Digital Filter;Wavelet Filter;Independent Component Analysis;Tensor Decomposition;Nonnegative Tensor Factorization;Time-Frequency Representation
Category: Technology & Engineering

Advanced Signal Processing For The Identification And Diagnosis Of The Condition Of Rotating Machinery

Author : Peeters Cédric
ISBN : OCLC:1191901268
Genre :
File Size : 79.42 MB
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This Ph.D. dissertation targets innovative methods for vibration-based condition monitoring of rotating machinery. Substantial benefits can be achieved from an economical and a safety point of view using condition monitoring. One of the most popular methods to gather information about the state of machine parts is through the analysis of machine vibrations. Most of these vibrations are directly linked to periodical behavior of subsystems within the machine like e.g. rotating shafts, gears, rotating electrical fields, etc. This knowledge can be exploited to enable faultdependent processing schemes. This dissertation investigates how to implement and utilize these processing schemes and details the steps in such a procedure. Typically, the first prerequisite for advanced analysis is the availability of the instantaneous rotation speed. This speed needs to be known since most frequency-based analysis techniques assume stationary behavior. Knowledge of the speed thus allows for compensating speed fluctuations, for example through angular resampling of the vibration signal. While there are hardware-based solutions for speed estimation using angle encoders or tachometers, this thesis investigates the potential in vibration signals for speed estimation. After speed estimation and angular resampling, a common next step is to separate the signal into deterministic and stochastic components. The cepstrum editing procedure is examined for its efficacy and applicability. Afterwards, different filtering methods are inspected as to improve the signal-to-noise ratio of the signal content of interest. Existing methods using conventional criteria are investigated together with a novel blind filtering methodology. The final step in the multi-step processing scheme is to search for the potential fault. Statistical indicators can be calculated on the processed time domain signal and tracked over time to check for increases. In many cases, the fault signature exhibits cyclostationary behavior. Therefore this dissertation also examines different cyclostationary analysis techniques. Lastly, the performance of the different processing methods is validated on two experimental vibration data sets of wind turbine gearboxes.

Estimation Of Cortical Connectivity In Humans

Author : Laura Astolfi
ISBN : 9781598295320
Genre : Medical
File Size : 61.23 MB
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In the last ten years many different brain imaging devices have conveyed a lot of information about the brain functioning in different experimental conditions. In every case, the biomedical engineers, together with mathematicians, physicists and physicians are called to elaborate the signals related to the brain activity in order to extract meaningful and robust information to correlate with the external behavior of the subjects. In such attempt, different signal processing tools used in telecommunications and other field of engineering or even social sciences have been adapted and re-used in the neuroscience field. The present book would like to offer a short presentation of several methods for the estimation of the cortical connectivity of the human brain. The methods here presented are relatively simply to implement, robust and can return valuable information about the causality of the activation of the different cortical areas in humans using non invasive electroencephalographic recordings. The knowledge of such signal processing tools will enrich the arsenal of the computational methods that a engineer or a mathematician could apply in the processing of brain signals.Table of Contents: Introduction / Estimation of the Effective Connectivity from Stationary Data by Structural Equation Modeling / Estimation of the Functional Connectivity from Stationary Data by Multivariate Autoregressive Methods / Estimation of Cortical Activity by the use of Realistic Head Modeling / Application: Estimation of Connectivity from Movement-Related Potentials / Application to High-Resolution EEG Recordings in a Cognitive Task (Stroop Test) / Application to Data Related to the Intention of Limb Movements in Normal Subjects and in a Spinal Cord Injured Patient / The Instantaneous Estimation of the Time-Varying Cortical Connectivity by Adaptive Multivariate Estimators / Time-Varying Connectivity from Event-Related Potentials
Category: Medical

Advanced Signal Processing Techniques Applied To Power Systems Control And Analysis

Author : Zbigniew Leonowicz
ISBN : 3039361864
Genre :
File Size : 80.8 MB
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The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods.