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Author: Elizabeth Ren
Publisher: BoD – Books on Demand
ISBN: 3866287925
Category : Computers
Languages : en
Pages : 288
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Book Description
With increasing availability of computation power, digital signal analysis algorithms have the potential of evolving from the common framewise operational method to samplewise operations which offer more precision in time. This thesis discusses a set of methods with samplewise operations: local signal approximation via Recursive Least Squares (RLS) where a mathematical model is fit to the signal within a sliding window at each sample. Thereby both the signal models and cost windows are generated by Autonomous Linear State Space Models (ALSSMs). The modeling capability of ALSSMs is vast, as they can model exponentials, polynomials and sinusoidal functions as well as any linear and multiplicative combination thereof. The fitting method offers efficient recursions, subsample precision by way of the signal model and additional goodness of fit measures based on the recursively computed fitting cost. Classical methods such as standard Savitzky-Golay (SG) smoothing filters and the Short-Time Fourier Transform (STFT) are united under a common framework. First, we complete the existing framework. The ALSSM parameterization and RLS recursions are provided for a general function. The solution of the fit parameters for different constraint problems are reviewed. Moreover, feature extraction from both the fit parameters and the cost is detailed as well as examples of their use. In particular, we introduce terminology to analyze the fitting problem from the perspective of projection to a local Hilbert space and as a linear filter. Analytical rules are given for computation of the equivalent filter response and the steady-state precision matrix of the cost. After establishing the local approximation framework, we further discuss two classes of signal models in particular, namely polynomial and sinusoidal functions. The signal models are complementary, as by nature, polynomials are suited for time-domain description of signals while sinusoids are suited for the frequency-domain. For local approximation of polynomials, we derive analytical expressions for the steady-state covariance matrix and the linear filter of the coefficients based on the theory of orthogonal polynomial bases. We then discuss the fundamental application of smoothing filters based on local polynomial approximation. We generalize standard SG filters to any ALSSM window and introduce a novel class of smoothing filters based on polynomial fitting to running sums.
Author: Elizabeth Ren
Publisher: BoD – Books on Demand
ISBN: 3866287925
Category : Computers
Languages : en
Pages : 288
Get Book Here
Book Description
With increasing availability of computation power, digital signal analysis algorithms have the potential of evolving from the common framewise operational method to samplewise operations which offer more precision in time. This thesis discusses a set of methods with samplewise operations: local signal approximation via Recursive Least Squares (RLS) where a mathematical model is fit to the signal within a sliding window at each sample. Thereby both the signal models and cost windows are generated by Autonomous Linear State Space Models (ALSSMs). The modeling capability of ALSSMs is vast, as they can model exponentials, polynomials and sinusoidal functions as well as any linear and multiplicative combination thereof. The fitting method offers efficient recursions, subsample precision by way of the signal model and additional goodness of fit measures based on the recursively computed fitting cost. Classical methods such as standard Savitzky-Golay (SG) smoothing filters and the Short-Time Fourier Transform (STFT) are united under a common framework. First, we complete the existing framework. The ALSSM parameterization and RLS recursions are provided for a general function. The solution of the fit parameters for different constraint problems are reviewed. Moreover, feature extraction from both the fit parameters and the cost is detailed as well as examples of their use. In particular, we introduce terminology to analyze the fitting problem from the perspective of projection to a local Hilbert space and as a linear filter. Analytical rules are given for computation of the equivalent filter response and the steady-state precision matrix of the cost. After establishing the local approximation framework, we further discuss two classes of signal models in particular, namely polynomial and sinusoidal functions. The signal models are complementary, as by nature, polynomials are suited for time-domain description of signals while sinusoids are suited for the frequency-domain. For local approximation of polynomials, we derive analytical expressions for the steady-state covariance matrix and the linear filter of the coefficients based on the theory of orthogonal polynomial bases. We then discuss the fundamental application of smoothing filters based on local polynomial approximation. We generalize standard SG filters to any ALSSM window and introduce a novel class of smoothing filters based on polynomial fitting to running sums.
Author: Rüdiger W. Brause
Publisher: Springer
ISBN: 3540399496
Category : Computers
Languages : en
Pages : 327
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Book Description
It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zing patient data, even in smaller health care institutions, the need for a rational treatment of all these data emerged as well. Therefore, the need for data exchange and presentation systems grew also. The goal of the symposium is to collect all these relevant aspects together. It provides an international forum for the sharing and exchange of original re- arch results, ideas and practical experiences among researchers and application developers from di erent areas related to medical applications dealing with the analysis of medical data. After a thorough reviewing process, 33 high quality papers were selected from the 45 international submissions. These contributions provided the di erent - pects of the eld in order to represent us with an exciting program.
Author: Jose Mira
Publisher: Springer
ISBN: 3540457232
Category : Computers
Languages : en
Pages : 875
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Book Description
Underlying most of the IWANN calls for papers is the aim to reassume some of the motivations of the groundwork stages of biocybernetics and the later bionics formulations and to try to reconsider the present value of two basic questions. The?rstoneis:“Whatdoesneurosciencebringintocomputation(thenew bionics)?” That is to say, how can we seek inspiration in biology? Titles such as “computational intelligence”, “arti?cial neural nets”, “genetic algorithms”, “evolutionary hardware”, “evolutive architectures”, “embryonics”, “sensory n- romorphic systems”, and “emotional robotics” are representatives of the present interest in “biological electronics” (bionics). Thesecondquestionis:“Whatcanreturncomputationtoneuroscience(the new neurocybernetics)?” That is to say, how can mathematics, electronics, c- puter science, and arti?cial intelligence help the neurobiologists to improve their experimental data modeling and to move a step forward towards the understa- ing of the nervous system? Relevant here are the general philosophy of the IWANN conferences, the sustained interdisciplinary approach, and the global strategy, again and again to bring together physiologists and computer experts to consider the common and pertinent questions and the shared methods to answer these questions.
Author: Jean-Daniel Fournier
Publisher:
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 344
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Book Description
This book - an outgrowth of a topical summer school - sets out to introduce non-specialists from physics and engineering to the basic mathematical concepts of approximation and Fourier theory. After a general introduction, Part II of this volume contains basic material on the complex and harmonic analysis underlying the further developments presented. Part III deals with the essentials of approximation theory while Part IV completes the foundations by a tour of probability theory. Part V reviews some major applications in signal and control theory. In Part VI mathematical aspects of dynamical systems theory are discussed. Part VII, finally, is devoted to a modern approach to two physics problems: turbulence and the control and noise analysis in gravitational waves measurements.
Author: Maged Marghany
Publisher: Elsevier
ISBN: 0443191565
Category : Science
Languages : en
Pages : 418
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Book Description
Synthetic Aperture Radar Image Processing Algorithms for Nonlinear Oceanic Turbulence and Front Modelling is both a research- and practice-based reference that bridges the gap between the remote sensing field and the dynamic oceanography exploration field. In this perspective, the book explicates how to apply techniques in synthetic aperture radar and quantum interferometry synthetic aperture radar (QInSAR) for oceanic turbulence and front simulation and modelling. The book includes detailed algorithms to enable readers to better understand and implement the practices covered in their own work and apply QInSAR to their own research.This multidisciplinary reference is useful for researchers and academics in dynamic oceanography and modelling, remote sensing and aquatic science, as well as geographers, geophysicists, and environmental engineers Details the potential of synthetic aperture radar in imaging ocean surface dynamical features Includes detailed algorithms and methods, allowing readers to develop their own computer algorithms Covers the latest applications of quantum image processing
Author: Yuhui Du
Publisher: Frontiers Media SA
ISBN: 2889634043
Category :
Languages : en
Pages : 288
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Book Description
There has been increasing interests in exploring biomarkers from brain images, aiming to have a better understanding and a more effective diagnosis of brain disorders such as schizophrenia, bipolar disorder, schizoaffective disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer’s disease and so on. Therefore, it is important to identify disease-specific changes for distinguishing healthy controls and patients with brain disorders as well as for differentiating patients with different disorders showing similar clinical symptoms. Biomarkers can be identified from different types of brain Imaging techniques including functional magnetic resonance imaging (fMRI), structural MRI, positron emission tomography (PET), electroencephalography (EEG), and magnetoencephalography (MEG) by using statistical analysis methods. Furthermore, based on measures from brain imaging techniques, machine learning techniques can help to classify or predict disease for individual subjects. In fact, fusion of features from multiple modalities may benefit the understanding of disease mechanism and improve the classification performance. This Research Topic further explores the functional or structural alterations in brain disorders.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 456
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Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author:
Publisher:
ISBN:
Category : Mechanics, Applied
Languages : en
Pages : 916
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Book Description
Author:
Publisher:
ISBN:
Category : Electrical engineering
Languages : en
Pages : 2304
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Book Description
Author: Antonio Tornambe
Publisher: World Scientific
ISBN: 9814632465
Category :
Languages : en
Pages : 863
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Book Description
This volume gathers together all the lectures presented at the 6th IEEE Mediterranean Conference. It focuses on the mathematical aspects in the theory and practice of control and systems, including stability and stabilizability, robust control, adaptive control, robotics and manufacturing; these topics are under intense investigation and development in the engineering and mathematics communities. The volume should have immediate appeal for a large group of engineers and mathematicians who are interested in very abstract as well as very concrete aspects of control and system theory.
