Signal Processing And Data Analysis
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Signal Processing And Data Analysis
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Author : Tianshuang Qiu
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2018-07-09
Signal Processing And Data Analysis written by Tianshuang Qiu and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-09 with Technology & Engineering categories.
This book presents digital signal processing theories and methods and their applications in data analysis, error analysis and statistical signal processing. Algorithms and Matlab programming are included to guide readers step by step in dealing with practical difficulties. Designed in a self-contained way, the book is suitable for graduate students in electrical engineering, information science and engineering in general.
Foundations Of Digital Signal Processing And Data Analysis
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Author : James A. Cadzow
language : en
Publisher: Macmillan Publishing Company
Release Date : 1987-01
Foundations Of Digital Signal Processing And Data Analysis written by James A. Cadzow and has been published by Macmillan Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-01 with Technology & Engineering categories.
Foundations Of Digital Signal Processing And Data Analysis
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Author : James A. Cadzow
language : en
Publisher:
Release Date : 1987
Foundations Of Digital Signal Processing And Data Analysis written by James A. Cadzow and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Signal processing categories.
Machine Intelligence Techniques For Data Analysis And Signal Processing
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Author : Dilip Singh Sisodia
language : en
Publisher: Springer Nature
Release Date : 2023-05-30
Machine Intelligence Techniques For Data Analysis And Signal Processing written by Dilip Singh Sisodia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-30 with Technology & Engineering categories.
This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, and videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves a valuable resource for those in academia and industry.
Signal Processing And Machine Learning For Biomedical Big Data
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Author : Ervin Sejdic
language : en
Publisher: CRC Press
Release Date : 2018-07-04
Signal Processing And Machine Learning For Biomedical Big Data written by Ervin Sejdic and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Medical categories.
Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.
Data Analysis And Signal Processing In Chromatography
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Author : A. Felinger
language : en
Publisher: Elsevier
Release Date : 1998-05-19
Data Analysis And Signal Processing In Chromatography written by A. Felinger and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-05-19 with Science categories.
This book gives an overview of the numerical data analysis and signal treatment techniques that are used in chromatography and related separation techniques. Emphasis is given to the description of the symmetrical and asymmetrical chromatographic peak shape models. Both theoretical and empirical models are discussed. The fundamentals of data acquisition, types and effect of baseline noise, and methods of improving the signal-to-noise ratio (either in time or in frequency and wavelet domain) are thoroughly discussed. Resolution enhancement techniques, such as curve fitting, deconvolution by Fourier and wavelet transforms, iterative deconvolution, Kalman filtering and multivariate methods of curve resolution are all discussed with several chromatographic examples. Quantitative analysis by peak area of peak height measurement, the precision and accuracy of the quantitation of stand-alone or overlapping and symmetrical or asymmetrical peaks are treated. In a separate chapter, guidelines are given for the use of transform techniques for the analysis of chromatograms. A statistical description of peak overlap is given in the final chapters. Since the concept of resolution has to be reconsidered when one separates complex mixtures, the problem of resolution and overlap is quantitatively discussed by means of statistical methods, and by using Fourier analysis of the complex chromatogram. Features of this book • The ultimate source of numerical techniques to enhance chromatographic data • Gives a detailed description of signal and resolution enhancement techniques in a manner applicable for enhancing not only chromatography, but also spectroscopic and other analytical signals • The first book with a thorough overview of the statistics of peak overlap. This is the first volume to encompass both the simple and more sophisticated methods for the numerical treatment of chromatograms. It is, therefore, the fundamental resource of numerical analysis methods for every analyst.
Statistical Signal Processing
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Author : Swagata Nandi
language : en
Publisher: Springer Nature
Release Date : 2020-08-21
Statistical Signal Processing written by Swagata Nandi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-21 with Computers categories.
This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.
Music Data Analysis
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Author : Claus Weihs
language : en
Publisher: CRC Press
Release Date : 2016-11-17
Music Data Analysis written by Claus Weihs and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-17 with Business & Economics categories.
This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.
Signals And Systems In Biomedical Engineering
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Author : Suresh R. Devasahayam
language : en
Publisher: Springer Science & Business Media
Release Date : 2000
Signals And Systems In Biomedical Engineering written by Suresh R. Devasahayam and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Biological models categories.
This book fills a critical gap in biomedical data analysis in making the connection between signal processing and physiological modelling. Based on the premise that the use of signal processing techniques is predicated on explicit or implicit models, this book provides a foundation in systems analysis and signal processing techniques for physiological data. The book comprises two main parts: namely, signal processing techniques for linear systems, and physiological modelling. Beginning with a broad introduction to signals and systems, the book proceeds to contemporary techniques in digital signal processing. While maintaining continuity of mathematical concepts, the emphasis is on practical implementation and applications. The signal processing topics covered include Fourier transform, the wavelet transform, and optimal filtering techniques. The book presumes only knowledge of college mathematics and is suitable for a beginner in the subject; however, a student with a previous course in analog and digital signal processing will find that only a third of the book contains a bare treatment of classical signal processing.
Signal Processing Driven Machine Learning Techniques For Cardiovascular Data Processing
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Author : Rajesh Kumar Tripathy
language : en
Publisher: Elsevier
Release Date : 2024-06-17
Signal Processing Driven Machine Learning Techniques For Cardiovascular Data Processing written by Rajesh Kumar Tripathy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-17 with Computers categories.
Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular data analysis. Topics in this book include machine learning methods such as supervised learning, unsupervised learning, semi-supervised learning, and meta-learning combined with different signal processing techniques such as multivariate data analysis, time-frequency analysis, multiscale analysis, and feature extraction techniques for the detection of cardiovascular diseases, heart valve disorders, hypertension, and activity monitoring using ECG, PPG, and PCG signals. In addition, this book also includes the applications of digital signal processing (time-frequency analysis, multiscale decomposition, feature extraction, non-linear analysis, and transform domain methods), machine learning and deep learning (convolutional neural network (CNN), recurrent neural network (RNN), transformer and attention-based models, etc.) techniques for the analysis of cardiac signals. The interpretable machine learning and deep learning models combined with signal processing for cardiovascular data analysis are also covered. Provides details regarding the application of various signal processing and machine learning-based methods for cardiovascular signal analysis Covers methodologies as well as experimental results and studies Helps readers understand the use of different cardiac signals such as ECG, PCG, and PPG for the automated detection of heart ailments and other related biomedical applications