Electrical & Electronics Abstracts PDF Download

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Publisher:
ISBN:
Category : Electrical engineering
Languages : en
Pages : 1904

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Author: C. A. Brebbia
Publisher: WIT Press
ISBN: 1845640896
Category : Technology & Engineering
Languages : en
Pages : 353

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Book Description
Projections for advances in medical and biological technology will transform medical care and treatment. This is in great part due to the results of interaction and collaborations between the medical sciences and engineering. These advances will result in substantial progressions in health care and in the quality of life of the population.Computer models in particular have been increasingly successful in simulating biological phenomena. These are lending support to many applications, including amongst others cardiovascular systems, the study of orthopaedics and biomechanics, electrical simulation. Another important contribution, due to the wide availability of computational facilities and the development of better numerical algorithms, is the ability to acquire analyses, manage and visualise massive amounts of data. Containing papers presented at the Seventh International Conference on Modelling in Medicine and Biology, this book covers a broad range of topics which will be of particular interest to medical and physical scientists and engineers interested in the latest developments in simulations in medicine. It will also be relevant to professionals working in medical enterprises which are actively involved in this field. Topics include: Cardiovascular Systems; Simulations in Surgery; Biomechanics; Advanced Technology in Dentistry; Simulation of Physiological Processes; Neural Systems; Computational Fluid Dynamics in Biomedicine; Orthopaedics and Bone Mechanics; Data Acquisition and Analysis; Virtual Reality in Medicine; Expert Systems in Medicine; Design and Simulation of Artificial Organs.

Author: Sandro Augusto Pavlik Haddad
Publisher: Springer Science & Business Media
ISBN: 1402090730
Category : Technology & Engineering
Languages : en
Pages : 221

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Often WT systems employ the discrete wavelet transform, implemented on a digital signal processor. However, in ultra low-power applications such as biomedical implantable devices, it is not suitable to implement the WT by means of digital circuitry due to the relatively high power consumption associated with the required A/D converter. Low-power analog realization of the wavelet transform enables its application in vivo, e.g. in pacemakers, where the wavelet transform provides a means to extremely reliable cardiac signal detection. In Ultra Low-Power Biomedical Signal Processing we present a novel method for implementing signal processing based on WT in an analog way. The methodology presented focuses on the development of ultra low-power analog integrated circuits that implement the required signal processing, taking into account the limitations imposed by an implantable device.

Author: Amir-Homayoon Najmi
Publisher: McGraw Hill Professional
ISBN: 1260458946
Category : Technology & Engineering
Languages : en
Pages : 353

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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

Author: Sushruta Mishra
Publisher: Springer Nature
ISBN: 3030979296
Category : Technology & Engineering
Languages : en
Pages : 487

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With rise of smart medical sensors, cloud computing and the health care technologies, “connected health” is getting remarkable consideration everywhere. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality. Cloud computing fits well in this scenario as it can provide high quality of clinical experience. Thus an IoT-cloud convergence can play a vital role in healthcare by offering better insight of heterogeneous healthcare content supporting quality care. It can also support powerful processing and storage facilities of huge data to provide automated decision making. This book aims to report quality research on recent advances towards IoT-Cloud convergence for smart healthcare, more specifically to the state-of-the-art approaches, design, development and innovative use of those convergence methods for providing insights into healthcare service demands. Students, researchers, and medical experts in the field of information technology, medicine, cloud computing, soft computing technologies, IoT and the related fields can benefit from this handbook in handling real-time challenges in healthcare. Current books are limited to focus either on soft computing algorithms or smart healthcare. Integration of smart and cloud computing models in healthcare resulting in connected health is explored in detail in this book.

Author: Abdulhamit Subasi
Publisher: Academic Press
ISBN: 0128176733
Category : Medical
Languages : en
Pages : 458

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. - Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction - Explains how to apply machine learning techniques to EEG, ECG and EMG signals - Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

Author:
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ISBN:
Category : American literature
Languages : en
Pages : 3310

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Author: Amir-Homayoon Najmi
Publisher: JHU Press
ISBN: 1421405598
Category : Mathematics
Languages : en
Pages : 303

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Introduced nearly three decades ago as a variable resolution alternative to the Fourier transform, a wavelet is a short oscillatory waveform for analysis of transients. The discrete wavelet transform has remarkable multi-resolution and energy-compaction properties. Amir-Homayoon Najmi’s introduction to wavelet theory explains this mathematical concept clearly and succinctly. Wavelets are used in processing digital signals and imagery from myriad sources. They form the backbone of the JPEG2000 compression standard, and the Federal Bureau of Investigation uses biorthogonal wavelets to compress and store its vast database of fingerprints. Najmi provides the mathematics that demonstrate how wavelets work, describes how to construct them, and discusses their importance as a tool to investigate and process signals and imagery. He reviews key concepts such as frames, localizing transforms, orthogonal and biorthogonal bases, and multi-resolution. His examples include the Haar, the Shannon, and the Daubechies families of orthogonal and biorthogonal wavelets. Our capacity and need for collecting and transmitting digital data is increasing at an astonishing rate. So too is the importance of wavelets to anyone working with and analyzing digital data. Najmi’s primer will be an indispensable resource for those in computer science, the physical sciences, applied mathematics, and engineering who wish to obtain an in-depth understanding and working knowledge of this fascinating and evolving field.

Author: Mihail C. Roco
Publisher: Springer Science & Business Media
ISBN: 9401703590
Category : Technology & Engineering
Languages : en
Pages : 477

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M. C. Roco and W.S. Bainbridge In the early decades of the 21st century, concentrated efforts can unify science based on the unity of nature, thereby advancing the combination of nanotechnology, biotechnology, information technology, and new technologies based in cognitive science. With proper attention to ethical issues and societal needs, converging in human abilities, societal technologies could achieve a tremendous improvement outcomes, the nation's productivity, and the quality of life. This is a broad, cross cutting, emerging and timely opportunity of interest to individuals, society and humanity in the long term. The phrase "convergent technologies" refers to the synergistic combination of four major "NBIC" (nano-bio-info-cogno) provinces of science and technology, each of which is currently progressing at a rapid rate: (a) nanoscience and nanotechnology; (b) biotechnology and biomedicine, including genetic engineering; (c) information technology, including advanced computing and communications; (d) cognitive science, including cognitive neuroscience. Timely and Broad Opportunity. Convergence of diverse technologies is based on material unity at the nanoscale and on technology integration from that scale.

Author: Simon Haykin
Publisher: John Wiley & Sons
ISBN: 9780470487051
Category : Science
Languages : en
Pages : 924

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A handbook on recent advancements and the state of the art in array processing and sensor Networks Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks. Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks. Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.