Optimization by Vector Space Methods

Author: David G. Luenberger

Publisher: John Wiley & Sons

ISBN: 9780471181170

Category: Mathematics

Page: 326

View: 2212

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Engineers must make decisions regarding the distribution of expensive resources in a manner that will be economically beneficial. This problem can be realistically formulated and logically analyzed with optimization theory. This book shows engineers how to use optimization theory to solve complex problems. Unifies the large field of optimization with a few geometric principles. Covers functional analysis with a minimum of mathematics. Contains problems that relate to the applications in the book.
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Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control

Author: Christian Kirches

Publisher: Springer Science & Business Media

ISBN: 383488202X

Category: Computers

Page: 367

View: 9629

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Christian Kirches develops a fast numerical algorithm of wide applicability that efficiently solves mixed-integer nonlinear optimal control problems. He uses convexification and relaxation techniques to obtain computationally tractable reformulations for which feasibility and optimality certificates can be given even after discretization and rounding.
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Applications of Space-Time Adaptive Processing

Author: Richard Klemm,Institution of Electrical Engineers

Publisher: IET

ISBN: 0852969244

Category: Technology & Engineering

Page: 919

View: 7413

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This text discusses various applications of space-time adaptive processing, including applications in OTH-radar, ground target tracking, STAP in real world clutter environments, jammer cancellation, superresolution, active sonar, seismics and communications. It is divided into two parts: the first dealing with the classical adaptive suppression of airborne and spacebased radar clutter, and the second comprising of miscellaneous applications in other fields such as communications, underwater sound and seismics.
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An Introduction to Optimization

Author: Edwin K. P. Chong,Stanislaw H. Zak

Publisher: John Wiley & Sons

ISBN: 0471654000

Category: Mathematics

Page: 496

View: 5492

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A modern, up-to-date introduction to optimization theory andmethods This authoritative book serves as an introductory text tooptimization at the senior undergraduate and beginning graduatelevels. With consistently accessible and elementary treatment ofall topics, An Introduction to Optimization, Second Edition helpsstudents build a solid working knowledge of the field, includingunconstrained optimization, linear programming, and constrainedoptimization. Supplemented with more than one hundred tables and illustrations,an extensive bibliography, and numerous worked examples toillustrate both theory and algorithms, this book alsoprovides: * A review of the required mathematical background material * A mathematical discussion at a level accessible to MBA andbusiness students * A treatment of both linear and nonlinear programming * An introduction to recent developments, including neuralnetworks, genetic algorithms, and interior-point methods * A chapter on the use of descent algorithms for the training offeedforward neural networks * Exercise problems after every chapter, many new to thisedition * MATLAB(r) exercises and examples * Accompanying Instructor's Solutions Manual available onrequest An Introduction to Optimization, Second Edition helps studentsprepare for the advanced topics and technological developments thatlie ahead. It is also a useful book for researchers andprofessionals in mathematics, electrical engineering, economics,statistics, and business. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.
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Acoustical Sensing and Imaging

Author: Hua Lee

Publisher: CRC Press

ISBN: 1498725740

Category: Technology & Engineering

Page: 122

View: 5417

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For complex operating modalities and dimensionalities, the design and development of high-performance sensing and imaging systems represent the most direct and significant advances in the field of system analysis and signal processing. In this field, the core components are physical modeling, mathematical analysis, formulation of image reconstruction algorithms, performance evaluation, and system optimization. Acoustical Sensing and Imaging covers the full scope of these components, with an emphasis on the applications of system analysis and signal processing in acoustical sensing and imaging. Providing a unified theoretical framework, this book: Focuses on the resolution analysis in the physical modeling of the systems, conducting the analysis through the quantitative assessment of the spatial-frequency spectral coverage Addresses the key elements of signal processing, such as the design of the probing waveforms, image reconstruction algorithms, error reduction and removal, and image enhancement Formulates the image reconstruction algorithms based on the concept of coherent backward propagation, in the form of multi-frequency tomography Explains how to improve system performance, including the correction of quadrature phase errors prior to image reconstruction and enhancement with coherent wavefield statistics during the superposition of sub-images Presents several applications as examples of various operating modalities, illustrating the technical and educational significance of the field Acoustical Sensing and Imaging ensures a broad appreciation of the design concepts, analysis, and development of high-performance sensing and imaging systems.
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Knowledge Discovery with Support Vector Machines

Author: Lutz H. Hamel

Publisher: John Wiley & Sons

ISBN: 1118211030

Category: Computers

Page: 246

View: 6291

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An easy-to-follow introduction to support vector machines This book provides an in-depth, easy-to-follow introduction to support vector machines drawing only from minimal, carefully motivated technical and mathematical background material. It begins with a cohesive discussion of machine learning and goes on to cover: Knowledge discovery environments Describing data mathematically Linear decision surfaces and functions Perceptron learning Maximum margin classifiers Support vector machines Elements of statistical learning theory Multi-class classification Regression with support vector machines Novelty detection Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas.
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