Higher Order Dynamic Mode Decomposition and Its Applications

Higher Order Dynamic Mode Decomposition and Its Applications
Author: Jose Manuel Vega,Soledad Le Clainche
Publsiher: Academic Press
Total Pages: 320
Release: 2020-09-30
ISBN 10: 0128227664
ISBN 13: 9780128227664
Language: EN, FR, DE, ES & NL

Higher Order Dynamic Mode Decomposition and Its Applications Book Review:

Higher Order Dynamic Mode Decomposition and Its Applications provides detailed background theory, as well as several fully explained applications from a range of industrial contexts to help readers understand and use this innovative algorithm. Data-driven modelling of complex systems is a rapidly evolving field, which has applications in domains including engineering, medical, biological, and physical sciences, where it is providing ground-breaking insights into complex systems that exhibit rich multi-scale phenomena in both time and space. Starting with an introductory summary of established order reduction techniques like POD, DEIM, Koopman, and DMD, this book proceeds to provide a detailed explanation of higher order DMD, and to explain its advantages over other methods. Technical details of how the HODMD can be applied to a range of industrial problems will help the reader decide how to use the method in the most appropriate way, along with example MATLAB codes and advice on how to analyse and present results. Includes instructions for the implementation of the HODMD, MATLAB codes, and extended discussions of the algorithm Includes descriptions of other order reduction techniques, and compares their strengths and weaknesses Provides examples of applications involving complex flow fields, in contexts including aerospace engineering, geophysical flows, and wind turbine design

14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)

14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)
Author: Francisco Martínez Álvarez,Alicia Troncoso Lora,José António Sáez Muñoz,Héctor Quintián,Emilio Corchado
Publsiher: Springer
Total Pages: 609
Release: 2019-04-30
ISBN 10: 3030200558
ISBN 13: 9783030200558
Language: EN, FR, DE, ES & NL

14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) Book Review:

This book includes 57 papers presented at the SOCO 2019 conference held in the historic city of Seville (Spain), in May 2019. Soft computing represents a set of computational techniques in machine learning, computer science and various engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. The selection of papers was extremely rigorous in order to maintain the high quality of the conference, which featured a number of special sessions, including sessions on: Soft Computing Methods in Manufacturing and Management Systems; Soft Computing Applications in the Field of Industrial and Environmental Enterprises; Optimization, Modeling and Control by Soft Computing Techniques; and Soft Computing in Aerospace, Mechanical and Civil Engineering: New methods and Industrial Applications.

Dynamic Mode Decomposition

Dynamic Mode Decomposition
Author: J. Nathan Kutz,Steven L. Brunton,Bingni W. Brunton,Joshua L. Proctor
Publsiher: SIAM
Total Pages: 234
Release: 2016-11-23
ISBN 10: 1611974496
ISBN 13: 9781611974492
Language: EN, FR, DE, ES & NL

Dynamic Mode Decomposition Book Review:

Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.

IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018

IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018
Author: Jörg Fehr,Bernard Haasdonk
Publsiher: Springer
Total Pages: 222
Release: 2019-07-19
ISBN 10: 3030210138
ISBN 13: 9783030210137
Language: EN, FR, DE, ES & NL

IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018 Book Review:

This volume contains the proceedings of the IUTAM Symposium on Model Order Reduction of Coupled System, held in Stuttgart, Germany, May 22–25, 2018. For the understanding and development of complex technical systems, such as the human body or mechatronic systems, an integrated, multiphysics and multidisciplinary view is essential. Many problems can be solved within one physical domain. For the simulation and optimization of the combined system, the different domains are connected with each other. Very often, the combination is only possible by using reduced order models such that the large-scale dynamical system is approximated with a system of much smaller dimension where the most dominant features of the large-scale system are retained as much as possible. The field of model order reduction (MOR) is interdisciplinary. Researchers from Engineering, Mathematics and Computer Science identify, explore and compare the potentials, challenges and limitations of recent and new advances.

Data Analysis for Direct Numerical Simulations of Turbulent Combustion

Data Analysis for Direct Numerical Simulations of Turbulent Combustion
Author: Heinz Pitsch,Antonio Attili
Publsiher: Springer Nature
Total Pages: 292
Release: 2020-05-28
ISBN 10: 3030447189
ISBN 13: 9783030447182
Language: EN, FR, DE, ES & NL

Data Analysis for Direct Numerical Simulations of Turbulent Combustion Book Review:

This book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data. The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics, applied mathematics, and the environmental and atmospheric sciences.

Technology and Science for the Ships of the Future

Technology and Science for the Ships of the Future
Author: A. Marinò,V. Bucci
Publsiher: IOS Press
Total Pages: 1076
Release: 2018-06-22
ISBN 10: 1614998701
ISBN 13: 9781614998709
Language: EN, FR, DE, ES & NL

Technology and Science for the Ships of the Future Book Review:

In 1974, a scientific conference covering marine automation group and large vessels issues was organized under the patronage of the Technical Naval Studies Centre (CETENA) and the Italian National Research Council (CNR). A later collaboration with the Marine Technical Association (ATENA) led to the renaming of the conference as NAV, extending the topics covered to the technical field previously covered by ATENA national conferences. The NAV conference is now held every 3 years, and attracts specialists from all over the world. This book presents the proceedings of NAV 2018, held in Trieste, Italy, in June 2018. The book contains 70 scientific papers, 35 technical papers and 16 reviews, and subjects covered include: comfort on board; conceptual and practical ship design; deep sea mining and marine robotics; protection of the environment; renewable marine energy; design and engineering of offshore vessels; digitalization, unmanned vehicles and cyber security; yacht and pleasure craft design and inland waterway vessels. With its comprehensive coverage of scientific and technical maritime issues, the book will be of interest to all those involved in this important industry.

Handbook of Robust Low-Rank and Sparse Matrix Decomposition

Handbook of Robust Low-Rank and Sparse Matrix Decomposition
Author: Thierry Bouwmans,Necdet Serhat Aybat,El-hadi Zahzah
Publsiher: CRC Press
Total Pages: 520
Release: 2016-09-20
ISBN 10: 1315353539
ISBN 13: 9781315353531
Language: EN, FR, DE, ES & NL

Handbook of Robust Low-Rank and Sparse Matrix Decomposition Book Review:

Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.

Data-Driven Science and Engineering

Data-Driven Science and Engineering
Author: Steven L. Brunton,J. Nathan Kutz
Publsiher: Cambridge University Press
Total Pages: 500
Release: 2019-02-28
ISBN 10: 1108422098
ISBN 13: 9781108422093
Language: EN, FR, DE, ES & NL

Data-Driven Science and Engineering Book Review:

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

Hilbert–Huang Transform and Its Applications

Hilbert–Huang Transform and Its Applications
Author: Norden E Huang,Samuel S P Shen
Publsiher: World Scientific
Total Pages: 400
Release: 2014-04-22
ISBN 10: 981450825X
ISBN 13: 9789814508254
Language: EN, FR, DE, ES & NL

Hilbert–Huang Transform and Its Applications Book Review:

This book is written for scientists and engineers who use HHT (Hilbert–Huang Transform) to analyze data from nonlinear and non-stationary processes. It can be treated as a HHT user manual and a source of reference for HHT applications. The book contains the basic principle and method of HHT and various application examples, ranging from the correction of satellite orbit drifting to detection of failure of highway bridges. The thirteen chapters of the first edition are based on the presentations made at a mini-symposium at the Society for Industrial and Applied Mathematics in 2003. Some outstanding mathematical research problems regarding HHT development are discussed in the first three chapters. The three new chapters of the second edition reflect the latest HHT development, including ensemble empirical mode decomposition (EEMD) and modified EMD. The book also provides a platform for researchers to develop the HHT method further and to identify more applications. Contents:Introduction to the Hilbert–Huang Transform and Its Related Mathematical ProblemsEnsemble Empirical Mode Decomposition and Its Multi-Dimensional ExtensionsMultivariate Extensions of Empirical Mode DecompositionB-Spline Based Empirical Mode DecompositionEMD Equivalent Filter Banks, From Interpretation to ApplicationsHHT Sifting and FilteringStatistical Significance Test of Intrinsic Mode FunctionsThe Time-Dependent Intrinsic CorrelationThe Application of Hilbert–Huang Transforms to Meteorological DatasetsEmpirical Mode Decomposition and Climate VariabilityEMD Correction of Orbital Drift Artifacts in Satellite Data StreamHHT Analysis of the Nonlinear and Non-Stationary Annual Cycle of Daily Surface Air Temperature DataHilbert Spectra of Nonlinear Ocean WavesEMD and Instantaneous Phase Detection of Structural DamageHTT-Based Bridge Structural Health-Monitoring MethodApplications of HHT in Image Analysis Readership: Applied mathematicians, climate scientists, highway engineers, medical scientists, geologists, civil engineers, mechanical engineers, electrical engineers, economics and graduate students in science or engineering. Keywords:Hilbert–Huang Transform;Empirical Mode Decomposition;Intrinsic Mode Function;Hilbert Spectral Analysis;Time-Frequency AnalysisKey Features:A tool book for analyzing nonlinear and non-stationary dataA source book for HHT development and applicationsThe most complete reference for HHT method and applications

Turbulence, Coherent Structures, Dynamical Systems and Symmetry

Turbulence, Coherent Structures, Dynamical Systems and Symmetry
Author: Philip Holmes
Publsiher: Cambridge University Press
Total Pages: 386
Release: 2012-02-23
ISBN 10: 1107008255
ISBN 13: 9781107008250
Language: EN, FR, DE, ES & NL

Turbulence, Coherent Structures, Dynamical Systems and Symmetry Book Review:

Describes methods revealing the structures and dynamics of turbulence for engineering, physical science and mathematics researchers working in fluid dynamics.

The Koopman Operator in Systems and Control

The Koopman Operator in Systems and Control
Author: Alexandre Mauroy,Igor Mezić,Yoshihiko Susuki
Publsiher: Springer Nature
Total Pages: 556
Release: 2020-02-22
ISBN 10: 3030357139
ISBN 13: 9783030357139
Language: EN, FR, DE, ES & NL

The Koopman Operator in Systems and Control Book Review:

This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory. The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts: theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification; data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; and Koopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control. A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.

Nonlinear and Adaptive Control with Applications

Nonlinear and Adaptive Control with Applications
Author: Alessandro Astolfi,Dimitrios Karagiannis,Romeo Ortega
Publsiher: Springer Science & Business Media
Total Pages: 290
Release: 2007-12-06
ISBN 10: 9781848000667
ISBN 13: 1848000669
Language: EN, FR, DE, ES & NL

Nonlinear and Adaptive Control with Applications Book Review:

The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.

Data-Driven Modeling & Scientific Computation

Data-Driven Modeling & Scientific Computation
Author: J. Nathan Kutz
Publsiher: OUP Oxford
Total Pages: 608
Release: 2013-08-08
ISBN 10: 019163588X
ISBN 13: 9780191635885
Language: EN, FR, DE, ES & NL

Data-Driven Modeling & Scientific Computation Book Review:

The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered in the sciences provide an incentive to develop mathematical techniques and computational algorithms that help synthesize, interpret and give meaning to the data in the context of its scientific setting. A specific aim of this book is to integrate standard scientific computing methods with data analysis. By doing so, it brings together, in a self-consistent fashion, the key ideas from: · statistics, · time-frequency analysis, and · low-dimensional reductions The blend of these ideas provides meaningful insight into the data sets one is faced with in every scientific subject today, including those generated from complex dynamical systems. This is a particularly exciting field and much of the final part of the book is driven by intuitive examples from it, showing how the three areas can be used in combination to give critical insight into the fundamental workings of various problems. Data-Driven Modeling and Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms for data manipulation and analysis. Emphasis is on the implementation of numerical schemes to practical problems in the engineering, biological and physical sciences. An accessible introductory-to-advanced text, this book fully integrates MATLAB and its versatile and high-level programming functionality, while bringing together computational and data skills for both undergraduate and graduate students in scientific computing.

Background Modeling and Foreground Detection for Video Surveillance

Background Modeling and Foreground Detection for Video Surveillance
Author: Thierry Bouwmans,Fatih Porikli,Benjamin Höferlin,Antoine Vacavant
Publsiher: CRC Press
Total Pages: 631
Release: 2014-07-25
ISBN 10: 1482205378
ISBN 13: 9781482205374
Language: EN, FR, DE, ES & NL

Background Modeling and Foreground Detection for Video Surveillance Book Review:

Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and low memory requirements. Incorporating both established and new ideas, Background Modeling and Foreground Detection for Video Surveillance provides a complete overview of the concepts, algorithms, and applications related to background modeling and foreground detection. Leaders in the field address a wide range of challenges, including camera jitter and background subtraction. The book presents the top methods and algorithms for detecting moving objects in video surveillance. It covers statistical models, clustering models, neural networks, and fuzzy models. It also addresses sensors, hardware, and implementation issues and discusses the resources and datasets required for evaluating and comparing background subtraction algorithms. The datasets and codes used in the text, along with links to software demonstrations, are available on the book’s website. A one-stop resource on up-to-date models, algorithms, implementations, and benchmarking techniques, this book helps researchers and industry developers understand how to apply background models and foreground detection methods to video surveillance and related areas, such as optical motion capture, multimedia applications, teleconferencing, video editing, and human–computer interfaces. It can also be used in graduate courses on computer vision, image processing, real-time architecture, machine learning, or data mining.

Numerical Linear Algebra

Numerical Linear Algebra
Author: Lloyd N. Trefethen,David Bau, III
Publsiher: SIAM
Total Pages: 361
Release: 1997-01-01
ISBN 10: 9780898719574
ISBN 13: 0898719577
Language: EN, FR, DE, ES & NL

Numerical Linear Algebra Book Review:

A concise, insightful, and elegant introduction to the field of numerical linear algebra. Designed for use as a stand-alone textbook in a one-semester, graduate-level course in the topic, it has already been class-tested by MIT and Cornell graduate students from all fields of mathematics, engineering, and the physical sciences. The authors' clear, inviting style and evident love of the field, along with their eloquent presentation of the most fundamental ideas in numerical linear algebra, make it popular with teachers and students alike.

Modeling Infectious Diseases in Humans and Animals

Modeling Infectious Diseases in Humans and Animals
Author: Matt J. Keeling,Pejman Rohani
Publsiher: Princeton University Press
Total Pages: 408
Release: 2011-09-19
ISBN 10: 1400841038
ISBN 13: 9781400841035
Language: EN, FR, DE, ES & NL

Modeling Infectious Diseases in Humans and Animals Book Review:

For epidemiologists, evolutionary biologists, and health-care professionals, real-time and predictive modeling of infectious disease is of growing importance. This book provides a timely and comprehensive introduction to the modeling of infectious diseases in humans and animals, focusing on recent developments as well as more traditional approaches. Matt Keeling and Pejman Rohani move from modeling with simple differential equations to more recent, complex models, where spatial structure, seasonal "forcing," or stochasticity influence the dynamics, and where computer simulation needs to be used to generate theory. In each of the eight chapters, they deal with a specific modeling approach or set of techniques designed to capture a particular biological factor. They illustrate the methodology used with examples from recent research literature on human and infectious disease modeling, showing how such techniques can be used in practice. Diseases considered include BSE, foot-and-mouth, HIV, measles, rubella, smallpox, and West Nile virus, among others. Particular attention is given throughout the book to the development of practical models, useful both as predictive tools and as a means to understand fundamental epidemiological processes. To emphasize this approach, the last chapter is dedicated to modeling and understanding the control of diseases through vaccination, quarantine, or culling. Comprehensive, practical introduction to infectious disease modeling Builds from simple to complex predictive models Models and methodology fully supported by examples drawn from research literature Practical models aid students' understanding of fundamental epidemiological processes For many of the models presented, the authors provide accompanying programs written in Java, C, Fortran, and MATLAB In-depth treatment of role of modeling in understanding disease control

Subspace Methods for System Identification

Subspace Methods for System Identification
Author: Tohru Katayama
Publsiher: Springer Science & Business Media
Total Pages: 392
Release: 2006-03-30
ISBN 10: 184628158X
ISBN 13: 9781846281587
Language: EN, FR, DE, ES & NL

Subspace Methods for System Identification Book Review:

An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts. Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closed-loop application of subspace identification methods. Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.

Modeling Atmospheric and Oceanic Flows

Modeling Atmospheric and Oceanic Flows
Author: Thomas von Larcher,Paul D. Williams
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2014-10-30
ISBN 10: 1118855922
ISBN 13: 9781118855928
Language: EN, FR, DE, ES & NL

Modeling Atmospheric and Oceanic Flows Book Review:

Modeling Atmospheric and Oceanic Flows: Insights from Laboratory Experiments and Numerical Simulations provides a broad overview of recent progress in using laboratory experiments and numerical simulations to model atmospheric and oceanic fluid motions. This volume not only surveys novel research topics in laboratory experimentation, but also highlights recent developments in the corresponding computational simulations. As computing power grows exponentially and better numerical codes are developed, the interplay between numerical simulations and laboratory experiments is gaining paramount importance within the scientific community. The lessons learnt from the laboratory–model comparisons in this volume will act as a source of inspiration for the next generation of experiments and simulations. Volume highlights include: Topics pertaining to atmospheric science, climate physics, physical oceanography, marine geology and geophysics Overview of the most advanced experimental and computational research in geophysics Recent developments in numerical simulations of atmospheric and oceanic fluid motion Unique comparative analysis of the experimental and numerical approaches to modeling fluid flow Modeling Atmospheric and Oceanic Flows will be a valuable resource for graduate students, researchers, and professionals in the fields of geophysics, atmospheric sciences, oceanography, climate science, hydrology, and experimental geosciences.

Time-Frequency Signal Analysis and Processing

Time-Frequency Signal Analysis and Processing
Author: Boualem Boashash
Publsiher: Academic Press
Total Pages: 1056
Release: 2015-12-11
ISBN 10: 0123985250
ISBN 13: 9780123985255
Language: EN, FR, DE, ES & NL

Time-Frequency Signal Analysis and Processing Book Review:

Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insights into how to use TFSAP methods to develop and implement the engineering application systems they require. New to this edition: New sections on Efficient and Fast Algorithms; a "Getting Started" chapter enabling readers to start using the algorithms on simulated and real examples with the TFSAP toolbox, compare the results with the ones presented in the book and then insert the algorithms in their own applications and adapt them as needed. Two new chapters and twenty three new sections, including updated references. New topics including: efficient algorithms for optimal TFDs (with source code), the enhanced spectrogram, time-frequency modelling, more mathematical foundations, the relationships between QTFDs and Wavelet Transforms, new advanced applications such as cognitive radio, watermarking, noise reduction in the time-frequency domain, algorithms for Time-Frequency Image Processing, and Time-Frequency applications in neuroscience (new chapter). A comprehensive tutorial introduction to Time-Frequency Signal Analysis and Processing (TFSAP), accessible to anyone who has taken a first course in signals Key advances in theory, methodology and algorithms, are concisely presented by some of the leading authorities on the respective topics Applications written by leading researchers showing how to use TFSAP methods

Chaos, Fractals, and Noise

Chaos, Fractals, and Noise
Author: Andrzej Lasota,Michael C. Mackey
Publsiher: Springer Science & Business Media
Total Pages: 474
Release: 2013-11-27
ISBN 10: 146124286X
ISBN 13: 9781461242864
Language: EN, FR, DE, ES & NL

Chaos, Fractals, and Noise Book Review:

The first edition of this book was originally published in 1985 under the ti tle "Probabilistic Properties of Deterministic Systems. " In the intervening years, interest in so-called "chaotic" systems has continued unabated but with a more thoughtful and sober eye toward applications, as befits a ma turing field. This interest in the serious usage of the concepts and techniques of nonlinear dynamics by applied scientists has probably been spurred more by the availability of inexpensive computers than by any other factor. Thus, computer experiments have been prominent, suggesting the wealth of phe nomena that may be resident in nonlinear systems. In particular, they allow one to observe the interdependence between the deterministic and probabilistic properties of these systems such as the existence of invariant measures and densities, statistical stability and periodicity, the influence of stochastic perturbations, the formation of attractors, and many others. The aim of the book, and especially of this second edition, is to present recent theoretical methods which allow one to study these effects. We have taken the opportunity in this second edition to not only correct the errors of the first edition, but also to add substantially new material in five sections and a new chapter.