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Author: Marc Wildi
Publisher: Springer Science & Business Media
ISBN: 3540269169
Category : Business & Economics
Languages : en
Pages : 283
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Book Description
The material contained in this book originated in interrogations about modern practice in time series analysis. • Why do we use models optimized with respect to one-step ahead foreca- ing performances for applications involving multi-step ahead forecasts? • Why do we infer 'long-term' properties (unit-roots) of an unknown process from statistics essentially based on short-term one-step ahead forecasting performances of particular time series models? • Are we able to detect turning-points of trend components earlier than with traditional signal extraction procedures? The link between 'signal extraction' and the first two questions above is not immediate at first sight. Signal extraction problems are often solved by su- ably designed symmetric filters. Towards the boundaries (t = 1 or t = N) of a time series a particular symmetric filter must be approximated by asymm- ric filters. The time series literature proposes an intuitively straightforward solution for solving this problem: • Stretch the observed time series by forecasts generated by a model. • Apply the symmetric filter to the extended time series. This approach is called 'model-based'. Obviously, the forecast-horizon grows with the length of the symmetric filter. Model-identification and estimation of unknown parameters are then related to the above first two questions. One may further ask, if this approximation problem and the way it is solved by model-based approaches are important topics for practical purposes? Consider some 'prominent' estimation problems: • The determination of the seasonally adjusted actual unemployment rate.
Author: Marc Wildi
Publisher: Springer Science & Business Media
ISBN: 3540269169
Category : Business & Economics
Languages : en
Pages : 283
Get Book Here
Book Description
The material contained in this book originated in interrogations about modern practice in time series analysis. • Why do we use models optimized with respect to one-step ahead foreca- ing performances for applications involving multi-step ahead forecasts? • Why do we infer 'long-term' properties (unit-roots) of an unknown process from statistics essentially based on short-term one-step ahead forecasting performances of particular time series models? • Are we able to detect turning-points of trend components earlier than with traditional signal extraction procedures? The link between 'signal extraction' and the first two questions above is not immediate at first sight. Signal extraction problems are often solved by su- ably designed symmetric filters. Towards the boundaries (t = 1 or t = N) of a time series a particular symmetric filter must be approximated by asymm- ric filters. The time series literature proposes an intuitively straightforward solution for solving this problem: • Stretch the observed time series by forecasts generated by a model. • Apply the symmetric filter to the extended time series. This approach is called 'model-based'. Obviously, the forecast-horizon grows with the length of the symmetric filter. Model-identification and estimation of unknown parameters are then related to the above first two questions. One may further ask, if this approximation problem and the way it is solved by model-based approaches are important topics for practical purposes? Consider some 'prominent' estimation problems: • The determination of the seasonally adjusted actual unemployment rate.
Author: Li Hu
Publisher: Springer Nature
ISBN: 9811391130
Category : Medical
Languages : en
Pages : 437
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Book Description
This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.
Author: Danilo Mandic
Publisher: Springer Science & Business Media
ISBN: 0387743677
Category : Technology & Engineering
Languages : en
Pages : 335
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Book Description
This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.
Author: Saeid Sanei
Publisher: John Wiley & Sons
ISBN: 1118691237
Category : Science
Languages : en
Pages : 312
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Book Description
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.
Author: Simon Braun
Publisher: John Wiley & Sons
ISBN: 9780470986783
Category : Science
Languages : en
Pages : 366
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Book Description
Signal processing is now a multidisciplinary topic, and one that has applications in many fields including, but not limited to, science, engineering, medicine, finance and the behavioural sciences. Modern software libraries that include dedicated languages and packages designed to simplify the development and application of signal processing techniques are now readily available; however this ease of application means that an understanding of the various techniques is imperative. It is critical that the student or practitioner is able to choose an appropriate processing technique, be aware of potential errors involved and understand how to control them. Discover Signal Processing exploits the rationale of “learning by doing”; actually attempting and performing a task is the most effective way to remember and understand. It presents the reader with a diverse range of exercises; some intended to recall or practice simple concepts, others more complex & aimed at developing a real understanding of the issues involved. These are accompanied by step-by-step explanations of the tools and techniques required. Provides systematic, organized and accessible instruction in a complex and mathematical subject. Stresses the understanding, selection and application of available signal processing techniques, as well as identification and control of error mechanisms; Includes more than 60 exercises covering major aspects of signal processing tools & geared at performing or testing specific tasks; Uses MATLAB as a platform, utilizing its extensive GUI capabilities enabling exercises to be performed using graphical elements only. Discover Signal Processing provides an excellent & accessible guide to signal processing for mechanical, aeronautical, civil and electronic engineers in their senior/ graduate year. It will also be of interest to those attending CPD courses as well as to practicing engineers.
Author: Adam Glowacz
Publisher: MDPI
ISBN: 3039282948
Category : Technology & Engineering
Languages : en
Pages : 604
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Book Description
This Special Issue with 35 published articles shows the significance of the topic “Signal Processing and Analysis of Electrical Circuit”. This topic has been gaining increasing attention in recent times. The presented articles can be categorized into four different areas: signal processing and analysis methods of electrical circuits; electrical measurement technology; applications of signal processing of electrical equipment; fault diagnosis of electrical circuits. It is a fact that the development of electrical systems, signal processing methods, and circuits has been accelerating. Electronics applications related to electrical circuits and signal processing methods have gained noticeable attention in recent times. The methods of signal processing and electrical circuits are widely used by engineers and scientists all over the world. The constituent papers represent a significant contribution to electronics and present applications that can be used in industry. Further improvements to the presented approaches are required for realizing their full potential.
Author: Tianshuang Qiu
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110465086
Category : Technology & Engineering
Languages : en
Pages : 602
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Book Description
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.
Author: Judee K. Burgoon
Publisher: Cambridge University Press
ISBN: 1108124585
Category : Computers
Languages : en
Pages : 441
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Book Description
Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outlines challenges and future perspectives for the benefit of experienced researchers and practitioners in the field.
Author: Xizhi Shi
Publisher: Springer Science & Business Media
ISBN: 3642113478
Category : Technology & Engineering
Languages : en
Pages : 381
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Book Description
"Blind Signal Processing: Theory and Practice" not only introduces related fundamental mathematics, but also reflects the numerous advances in the field, such as probability density estimation-based processing algorithms, underdetermined models, complex value methods, uncertainty of order in the separation of convolutive mixtures in frequency domains, and feature extraction using Independent Component Analysis (ICA). At the end of the book, results from a study conducted at Shanghai Jiao Tong University in the areas of speech signal processing, underwater signals, image feature extraction, data compression, and the like are discussed. This book will be of particular interest to advanced undergraduate students, graduate students, university instructors and research scientists in related disciplines. Xizhi Shi is a Professor at Shanghai Jiao Tong University.
Author: Xian-Da Zhang
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110475669
Category : Technology & Engineering
Languages : en
Pages : 457
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Book Description
The book systematically introduces theories of frequently-used modern signal processing methods and technologies, and focuses discussions on stochastic signal, parameter estimation, modern spectral estimation, adaptive filter, high-order signal analysis and non-linear transformation in time-domain signal analysis. With abundant exercises, the book is an essential reference for graduate students in electrical engineering and information science.
