Showing 73–96 of 158 results
Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics—including familiarity with Fourier series, matrices, probability, and statistics—this Second Edition: Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filtersExpands the material on Fourier analysis to three new chapters to provide additional background informationPresents real-world examples of applications that demonstrate how mathematics is used in remote sensingFeaturing problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.
This anthology explores six current approaches to the study of mind: the neuroscientific, the behavioral-experimental, the competence approach, the ecological, the phenomenological, and the computational. It is an organiz ing theme of the book that these approaches are interdependent, that they cannot and should not be pursued in provincial isolation from one another. All but two of the chapters were commissioned for this volume and appear here for the first time. The contributions of Paul Churchland and Brian Cantwell Smith have appeared elsewhere only recently.
This comprehensive textbook introduces readers to the principal ideas and applications of game theory, in a style that combines rigor with accessibility. Steven Tadelis begins with a concise description of rational decision making, and goes on to discuss strategic and extensive form games with complete information, Bayesian games, and extensive form games with imperfect information.
Inverse problems have been the focus of a growing number of research efforts over the last 40 years-and rightly so. The ability to determine a "cause" from an observed "effect" is a powerful one. Researchers now have at their disposal a variety of techniques for solving inverse problems, techniques that go well beyond those useful for relatively simple parameter estimation problems.
Several complete textbooks of mathematics on geometric optimal control theory exist in the literature, but little has been done with relevant applications in control engineering. This monograph is intended to fill this gap. It is based on graduate courses for mathematicians and physicists and presents results from two research projects in space mechanics and quantum control.
* Geometric optimal control theory: Pontryagin Maximum Principle and second order necessary and sufficient optimality conditions * Extensions of Riemannian geometry in optimal control theory * Optimal control in space mechanics * Application to the orbital transfer between elliptic orbits in the two and three body problem * Optimal control of dissipative quantum systems * Application in Nuclear Magnetic Resonance and Magnetic Resonance Imaging.
The presentation is self-contained and readers can use our techniques to perform similar analysis in their own problems.
the advantages of group theory in physics were not recognized till 1925 when it was applied for formal study of theoretical foundations of quantum mechanics, atomic structures and spectra by, to name a few, H A Bethe, E P Wigner, etc. It has now become indispensable in several branches of physics and physical chemistry. Dr. Joshi develops the mathematics of group theory and then goes on to present its applications to quantum mechanics, crystallography, and solid state physics. For proper comprehension of representation theory, he has covered thoroughly such diverse but relevant topics as Hilbert spaces, function spaces, operators, and direct sum and product of matrices.
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications.
This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals.
The contributions to this volume arose from talks presented at a symposium on the nonlinear partial differential equations of mathematical physics, which took place in New York City, April 20-23, 1964. The organizational work and invitations were the responsibility of a committee, consisting of C. B. Morrey, W. Noll, J. B. Serrin, A. H. Taub and myself as chairman. It was inevitable in view of the broad scope of the subject matter and the severe limitations of time that many important and original contributions could not be included in the program.
The Seventh Symposium in Applied Mathematics, sponsored by the American Mathematical Society and the Office of Ordnance Research, and devoted to Mathematical Probability and Its Applications, was held at the Polytechnic Institute of Brooklyn on April 14 and 15, 1955. This volume contains the papers (one in abstract form) which were presented at the Symposium. Prolonged consideration by the members of the Program Committee, under the chairmanship of Dr. H. W. Bode, resulted in the decision that the Symposium should be concerned with three principal themes, viz.,
This volume contains the proceedings of the 11th conference on AGC2T, held in Marseilles, France in November 2007. There are 12 original research articles covering asymptotic properties of global fields, arithmetic properties of curves and higher dimensional varieties, and applications to codes and cryptography. This volume also contains a survey article on applications of finite fields by J.-P. Serre. AGC2T conferences take place in Marseilles, France every 2 years. These international conferences have been a major event in the area of applied arithmetic geometry for more than 20 years.
The early development of graph theory was heavily motivated and influenced by topological and geometric themes, such as the Konigsberg Bridge Problem, Euler’s Polyhedral Formula, or Kuratowski’s characterization of planar graphs. In 1936, when Denes Konig published his classical ""Theory of Finite and Infinite Graphs"", the first book ever written on the subject, he stressed this connection by adding the subtitle Combinatorial Topology of Systems of Segments. He wanted to emphasize that the subject of his investigations was very concrete: planar figures consisting of points connected by straight-line segments.
Piecewise constant systems exist in widely expanded areas such as engineering, physics, and mathematics. Extraordinary and complex characteristics of piecewise constant systems have been reported in recent years. This book provides the methodologies for analyzing and assessing nonlinear piecewise constant systems on a theoretically and practically sound basis.
Wavelet theory had its origin in quantum field theory, signal analysis, and function space theory. In these areas wavelet-like algorithms replace the classical Fourier-type expansion of a function. This unique new book is an excellent introduction to the basic properties of wavelets, from background math to powerful applications. The authors provide elementary methods for constructing wavelets, and illustrate several new classes of wavelets.
Multidimensional scaling covers a variety of statistical techniques in the area of multivariate data analysis. Geared toward dimensional reduction and graphical representation of data, it arose within the field of the behavioral sciences, but now holds techniques widely used in many disciplines.
Evolution equations of hyperbolic or more general p-evolution type form an active field of current research. This volume aims to collect some recent advances in the area in order to allow a quick overview of ongoing research. The contributors are first rate mathematicians. This collection of research papers is centred around parametrix constructions and microlocal analysis; asymptotic constructions of solutions; energy and dispersive estimates; and associated spectral transforms. Applications concerning elasticity and general relativity complement the volume.
Covering some of the key areas of optimal control theory (OCT), a rapidly expanding field, the authors use new methods to set out a version of OCT’s more refined ‘maximum principle.’ The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games.
This book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control.
Exploring Linear Algebra: Labs and Projects with Mathematica® is a hands-on lab manual for daily use in the classroom. Each lab includes exercises, theorems, and problems that guide your students on an exploration of linear algebra.The exercises section integrates problems, technology, Mathematica® visualization, and Mathematica CDFs, enabling students to discover the theory and applications of linear algebra in a meaningful way. The theorems and problems section presents the theoretical aspects of linear algebra.
Designed for a one-semester course, Introduction to Numerical Analysis and Scientific Computing presents fundamental concepts of numerical mathematics and explains how to implement and program numerical methods. The classroom-tested text helps students understand floating point number representations, particularly those pertaining to IEEE simple and double-precision standards as used in scientific computer environments such as MATLAB® version 7.
Drawing on their years of teaching students in mathematics, engineering, and the sciences, the authors discuss computer arithmetic as a source for generating round-off errors and how to avoid the use of algebraic expression that may lead to loss of significant figures.
The finite element method has always been a mainstay for solving engineering problems numerically. The most recent developments in the field clearly indicate that its future lies in higher-order methods, particularly in higher-order hp-adaptive schemes.
This text is an addition to the existing literature about the symmetrical properties of sound waves. The authors clarify the algebraic and analytical nature of the dynamic acoustic problem. Operator equations which are typical for linear systems and the more general Lie method are considered, which can be applied even to nonlinear problems. The information obtained allows the reader to construct different types of analytical solutions of the different acoustic equation. The acoustic differential equation describes sound waves in elastic media.
This book provides an introduction to the mathematical theory of nonlinear control systems. It contains many topics that are usually scattered among different texts. The book also presents some topics of current research, which were never before included in a textbook. This volume will serve as an ideal textbook for graduate students. It is self-contained, with several appendices covering a wide mathematical background. Students will be aided by its lucid exposition. More than 100 figures and 100 exercises have been inserted, helping the readers to understand the key geometric ideas and build their intuition.
With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods, algorithms, and computations for fitting distributions to data. It also provides in-depth coverage of cutting-edge applications.The book begins with commentary by three GLD pioneers: John S.
This comprehensive, flexible text is used in both one- and two-semester courses to review introductory through intermediate statistics. Instructors select the topics that are most appropriate for their course. Its conceptual approach helps students more easily understand the concepts and interpret SPSS and research results. Key concepts are simply stated and occasionally reintroduced and related to one another for reinforcement. Numerous examples demonstrate their relevance. This edition features more explanation to increase understanding of the concepts.
Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
Showing 73–96 of 158 results