Higher Order Dynamic Mode Decomposition and Its Applications

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

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  • Author : Jose Manuel Vega
  • Publisher : Academic Press
  • Pages : 320 pages
  • ISBN : 0128227664
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKHigher Order Dynamic Mode Decomposition and Its Applications

Higher Order Dynamic Mode Decomposition and Its Applications

Higher Order Dynamic Mode Decomposition and Its Applications
  • Author : Jose Manuel Vega,Soledad Le Clainche
  • Publisher : Academic Press
  • Release : 30 September 2020
GET THIS BOOKHigher Order Dynamic Mode Decomposition and Its Applications

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

Dynamic Mode Decomposition

Dynamic Mode Decomposition
  • Author : J. Nathan Kutz,Steven L. Brunton,Bingni W. Brunton,Joshua L. Proctor
  • Publisher : SIAM
  • Release : 23 November 2016
GET THIS BOOKDynamic Mode Decomposition

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.

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

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  • Author : Francisco Martínez Álvarez,Alicia Troncoso Lora,José António Sáez Muñoz,Héctor Quintián,Emilio Corchado
  • Publisher : Springer
  • Release : 30 April 2019
GET THIS BOOK14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)

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

Hilbert–Huang Transform and Its Applications

Hilbert–Huang Transform and Its Applications
  • Author : Norden E Huang,Samuel S P Shen
  • Publisher : World Scientific
  • Release : 22 April 2014
GET THIS BOOKHilbert–Huang Transform and Its Applications

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

ScaLAPACK Users' Guide

ScaLAPACK Users' Guide
  • Author : L. S. Blackford,J. Choi,A. Cleary,E. D'Azevedo,J. Demmel,I. Dhillon,J. Dongarra,S. Hammarling,G. Henry,A. Petitet,K. Stanley,D. Walker,R. C. Whaley
  • Publisher : SIAM
  • Release : 16 May 1997
GET THIS BOOKScaLAPACK Users' Guide

ScaLAPACK is an acronym for Scalable Linear Algebra Package or Scalable LAPACK. It is a library of high-performance linear algebra routines for distributed memory message-passing MIMD computers and networks of workstations supporting parallel virtual machine (PVM) and/or message passing interface (MPI). It is a continuation of the LAPACK project, which designed and produced analogous software for workstations, vector supercomputers, and shared memory parallel computers. Both libraries contain routines for solving systems of linear equations, least squares problems, and eigenvalue

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
  • Publisher : CRC Press
  • Release : 20 September 2016
GET THIS BOOKHandbook of Robust Low-Rank and Sparse Matrix Decomposition

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

Shallow Flows

Shallow Flows
  • Author : Gerhard H. Jirka,Wim S.J. Uijttewaal
  • Publisher : Taylor & Francis
  • Release : 15 September 2004
GET THIS BOOKShallow Flows

This text presents the key findings of the International Symposium held in Delft in 2003, which explored the process of shallow flows. Shallow flows are found in lowland rivers, lakes, estuaries, bays, coastal areas and in density-stratified atmospheres, and may be observed in puddles, as in oceans. They impact on the life and work of a wide variety of readers, who are here provided with a clear overview of the subject. Shallow flows are intrinsically turbulent. On one hand, there are

An Introduction to Semi-tensor Product of Matrices and Its Applications

An Introduction to Semi-tensor Product of Matrices and Its Applications
  • Author : Daizhan Cheng,Hongsheng Qi,Yin Zhao
  • Publisher : World Scientific
  • Release : 16 May 2021
GET THIS BOOKAn Introduction to Semi-tensor Product of Matrices and Its Applications

Proposes a generalization of Conventional Matrix Product (CMP), called the Semi-Tensor Product (STP). This book offers a comprehensive introduction to the theory of STP and its various applications, including logical function, fuzzy control, Boolean networks, analysis and control of nonlinear systems, amongst others.

Stochastic Tools in Turbulence

Stochastic Tools in Turbulence
  • Author : John L. Lumey
  • Publisher : Elsevier
  • Release : 02 December 2012
GET THIS BOOKStochastic Tools in Turbulence

Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the characteristic function, and

Numerical Linear Algebra

Numerical Linear Algebra
  • Author : Lloyd N. Trefethen,David Bau, III
  • Publisher : SIAM
  • Release : 01 January 1997
GET THIS BOOKNumerical Linear Algebra

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

The Koopman Operator in Systems and Control

The Koopman Operator in Systems and Control
  • Author : Alexandre Mauroy,Igor Mezić,Yoshihiko Susuki
  • Publisher : Springer Nature
  • Release : 22 February 2020
GET THIS BOOKThe Koopman Operator in Systems and Control

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,

Computer Vision

Computer Vision
  • Author : Richard Szeliski
  • Publisher : Springer Science & Business Media
  • Release : 30 September 2010
GET THIS BOOKComputer Vision

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic

Process Dynamics and Control

Process Dynamics and Control
  • Author : Dale E. Seborg,Duncan A. Mellichamp,Thomas F. Edgar,Francis J. Doyle, III
  • Publisher : John Wiley & Sons
  • Release : 12 April 2010
GET THIS BOOKProcess Dynamics and Control

This third edition provides chemical engineers with process control techniques that are used in practice while offering detailed mathematical analysis. Numerous examples and simulations are used to illustrate key theoretical concepts. New exercises are integrated throughout several chapters to reinforce concepts. Up-to-date information is also included on real-time optimization and model predictive control to highlight the significant impact these techniques have on industrial practice. And chemical engineers will find two new chapters on biosystems control to gain the latest perspective