Publisher: Wiley
Language: English
ISBN: 0471696935
Paperback: 647 pages
Data: Jan 2008
Format: PDF
Description: Probability and Statistical Inference, Second Edition is a user-friendly book that stresses the comprehension of concepts instead of the simple acquisition of a skill or tool. It provides a mathematical framework that permits students to carry out various procedures using any number of computer software packages as opposed to relying on one particular package. Its unique approach to problems allows readers to integrate the knowledge gained from the text, thus, enhancing a more complete and honest understanding of the topic.
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Publisher: Springer
Language: English
ISBN: 0387372385
Paperback: 239 pages
Data: Apr 2008
Format: PDF
Description: Ultra Wideband Circuits, Transceivers and Systems is a compilation of chapters on various aspects of Ultra Wideband. The topics covered include: An overview of circuit techniques for broadband applications which provides a comparative analysis of various broadband implementations for different parts of the transceiver such as amplifiers, oscillators and filters. System proposals for Ultra Wideband: This material includes a historical perspective of the development of Ultra Wideband, starting with the earliest proposals to the FCC, and describing the current state of the art, including the OFDM and pulse based approaches to Ultra Wideband.
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Publisher: Wiley
Language: English
ISBN: 0470226544
Paperback: 184 pages
Data: Feb 2008
Format: PDF
Description: This new book by Donald Braben discusses in detail what Transformative Research (Venture Research) actually is, how it relates to other research programmers, how an initiative might be designed and implemented, how it might be supported on the national scale, and why it is important to everyone.
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Publisher: McGraw-Hill
Language: English
ISBN: 0071459499
Paperback: 412 pages
Data: Jun 2005
Format: PDF
Description: Now anyone can grasp the fundamentals of technical math — without formal training, unlimited time, or a genius IQ. In Technical Math Demystified, bestselling science writer Stan Gibilisco provides an effective, illuminating, and entertaining way to learn this complex subject.
This self-teaching guide first explains basic concepts such as linear, nonlinear, and multivariable equations, geometry, and coordinate systems. Then you’ll move on to logarithms, exponential functions, trigonometry, Boolean algebra, vectors, and single-variable calculus. Featuring end-of-chapter quizzes and a final exam, this book will teach you how to solve technical math problems in no time.
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Publisher: Morgan and Claypool Publishers
Language: English
ISBN: 1598295756
Paperback: 180 pages
Data: Feb 2008
Format: PDF
Description: Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vector linear prediction is explained in considerable detail and so is the theory of line spectral processes. This focus and its small size make the book different from many excellent texts which cover the topic, including a few that are actually dedicated to linear prediction. There are several examples and computer-based demonstrations of the theory. Applications are mentioned wherever appropriate, but the focus is not on the detailed development of these applications. The writing style is meant to be suitable for self-study as well as for classroom use at the senior and first-year graduate levels. The text is self-contained for readers with introductory exposure to signal processing, random processes, and the theory of matrices, and a historical perspective and detailed outline are given in the first chapter. Table of Contents: Introduction / The Optimal Linear Prediction Problem / Levinson’s Recursion / Lattice Structures for Linear Prediction / Autoregressive Modeling / Prediction Error Bound and Spectral Flatness / Line Spectral Processes / Linear Prediction Theory for Vector Processes / Appendix A: Linear Estimation of Random Variables / B: Proof of a Property of Autocorrelations / C: Stability of the Inverse Filter / Recursion Satisfied by AR Autocorrelations
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Publisher: Springer
Language: English
ISBN: 3540779736
Paperback: 386 pages
Data: Apr 2008
Format: PDF
Description: This well-accepted introduction to computational geometry is a textbook for high-level undergraduate and low-level graduate courses. The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms.
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Publisher: Springer
Language: English
ISBN: 3540434313
Paperback: 120 pages
Data: Dec 2005
Format: PDF
Description: Malliavin calculus provides an infinite-dimensional differential calculus in the context of continuous paths stochastic processes. The calculus includes formulae of integration by parts and Sobolev spaces of differentiable functions defined on a probability space. This new book, demonstrating the relevance of Malliavin calculus for Mathematical Finance, starts with an exposition from scratch of this theory. Greeks (price sensitivities) are reinterpreted in terms of Malliavin calculus. Integration by parts formulae provide stable Monte Carlo schemes for numerical valuation of digital options. Finite-dimensional projections of infinite-dimensional Sobolev spaces lead to Monte Carlo computations of conditional expectations useful for computing American options. The discretization error of the Euler scheme for a stochastic differential equation is expressed as a generalized Watanabe distribution on the Wiener space. Insider information is expressed as an infinite-dimensional drift. The last chapter gives an introduction to the same objects in the context of jump processes where incomplete markets appear.
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