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Advanced Mathematical and Computational Tools in Metrology VI
  • Language: en
  • Pages: 376

Advanced Mathematical and Computational Tools in Metrology VI

This volume collects refereed contributions based on the presentations made at the Sixth Workshop on Advanced Mathematical and Computational Tools in Metrology, held at the Istituto di Metrologia OC G. ColonnettiOCO (IMGC), Torino, Italy, in September 2003. It provides a forum for metrologists, mathematicians and software engineers that will encourage a more effective synthesis of skills, capabilities and resources, and promotes collaboration in the context of EU programmes, EUROMET and EA projects, and MRA requirements. It contains articles by an important, worldwide group of metrologists and mathematicians involved in measurement science and, together with the five previous volumes in this series, constitutes an authoritative source for the mathematical, statistical and software tools necessary to modern metrology. The proceedings have been selected for coverage in: . OCo Index to Scientific & Technical Proceedings- (ISTP- / ISI Proceedings). OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences."

Structured Matrices in Mathematics, Computer Science, and Engineering II
  • Language: en
  • Pages: 362

Structured Matrices in Mathematics, Computer Science, and Engineering II

"The collection of the contributions to these volumes offers a flavor of the plethora of different approaches to attack structured matrix problems. The reader will find that the theory of structured matrices is positioned to bridge diverse applications in the sciences and engineering, deep mathematical theories, as well as computational and numberical issues. The presentation fully illustrates the fact that the technicques of engineers, mathematicisn, and numerical analysts nicely complement each other, and they all contribute to one unified theory of structured matrices"--Back cover.

Low Rank Approximation
  • Language: en
  • Pages: 260

Low Rank Approximation

Data Approximation by Low-complexity Models details the theory, algorithms, and applications of structured low-rank approximation. Efficient local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. Much of the text is devoted to describing the applications of the theory including: system and control theory; signal processing; computer algebra for approximate factorization and common divisor computation; computer vision for image deblurring and segmentation; machine learning for information retrieval and clustering; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; and psychometrics for factor analysis. Software implementation of the methods is given, making the theory directly applicable in practice. All numerical examples are included in demonstration files giving hands-on experience and exercises and MATLAB® examples assist in the assimilation of the theory.

Textbook of Contemporary Neurosurgery (Volumes 1 & 2)
  • Language: en
  • Pages: 1882

Textbook of Contemporary Neurosurgery (Volumes 1 & 2)

This two volume set is a comprehensive guide to neurosurgery. Each section covers neurological disorders in different parts of the body, beginning with an introduction and ending with key practice points for quick review, integrating theory and practice. Genetics, ethics and physiotherapy are also discussed. With contributions from recognised specialists in the USA and Europe, this practical manual includes more than 1000 images and illustrations to assist learning and understanding. Key Features Comprehensive two volume set giving complete review of field of neurosurgery Covers numerous neurological disorders in different parts of the body Each section feature key practice points for quick review Integrates theory and practice More than 1000 images and illustrations Contributions from US and European specialists

Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling
  • Language: en
  • Pages: 404

Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling

  • Type: Book
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  • Published: 1997-01-01
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  • Publisher: SIAM

An overview of the computational issues; statistical, numerical, and algebraic properties, and new generalizations and applications of advances on TLS and EIV models. Experts from several disciplines prepared overview papers which were presented at the conference and are included in this book.

Modern Econometric Analysis
  • Language: en
  • Pages: 236

Modern Econometric Analysis

In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.

Blind Image Deconvolution
  • Language: en
  • Pages: 474

Blind Image Deconvolution

  • Type: Book
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  • Published: 2017-12-19
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  • Publisher: CRC Press

Blind image deconvolution is constantly receiving increasing attention from the academic as well the industrial world due to both its theoretical and practical implications. The field of blind image deconvolution has several applications in different areas such as image restoration, microscopy, medical imaging, biological imaging, remote sensing, astronomy, nondestructive testing, geophysical prospecting, and many others. Blind Image Deconvolution: Theory and Applications surveys the current state of research and practice as presented by the most recognized experts in the field, thus filling a gap in the available literature on blind image deconvolution. Explore the gamut of blind image deco...

Neural-Based Orthogonal Data Fitting
  • Language: en
  • Pages: 247

Neural-Based Orthogonal Data Fitting

The presentation of a novel theory in orthogonal regression The literature about neural-based algorithms is often dedicated to principal component analysis (PCA) and considers minor component analysis (MCA) a mere consequence. Breaking the mold, Neural-Based Orthogonal Data Fitting is the first book to start with the MCA problem and arrive at important conclusions about the PCA problem. The book proposes several neural networks, all endowed with a complete theory that not only explains their behavior, but also compares them with the existing neural and traditional algorithms. EXIN neurons, which are of the authors' invention, are introduced, explained, and analyzed. Further, it studies the a...

Matrices, Moments and Quadrature with Applications
  • Language: en
  • Pages: 376

Matrices, Moments and Quadrature with Applications

This computationally oriented book describes and explains the mathematical relationships among matrices, moments, orthogonal polynomials, quadrature rules, and the Lanczos and conjugate gradient algorithms. The book bridges different mathematical areas to obtain algorithms to estimate bilinear forms involving two vectors and a function of the matrix. The first part of the book provides the necessary mathematical background and explains the theory. The second part describes the applications and gives numerical examples of the algorithms and techniques developed in the first part. Applications addressed in the book include computing elements of functions of matrices; obtaining estimates of the error norm in iterative methods for solving linear systems and computing parameters in least squares and total least squares; and solving ill-posed problems using Tikhonov regularization. This book will interest researchers in numerical linear algebra and matrix computations, as well as scientists and engineers working on problems involving computation of bilinear forms.

Exact and Approximate Modeling of Linear Systems
  • Language: en
  • Pages: 210

Exact and Approximate Modeling of Linear Systems

  • Type: Book
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  • Published: 2006-01-31
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  • Publisher: SIAM

Exact and Approximate Modeling of Linear Systems: A Behavioral Approach elegantly introduces the behavioral approach to mathematical modeling, an approach that requires models to be viewed as sets of possible outcomes rather than to be a priori bound to particular representations. The authors discuss exact and approximate fitting of data by linear, bilinear, and quadratic static models and linear dynamic models, a formulation that enables readers to select the most suitable representation for a particular purpose. This book presents exact subspace-type and approximate optimization-based identification methods, as well as representation-free problem formulations, an overview of solution approaches, and software implementation. Readers will find an exposition of a wide variety of modeling problems starting from observed data. The presented theory leads to algorithms that are implemented in C language and in MATLAB.