Time Dependent Phase Space Filters
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Time Dependent Phase Space Filters
This book introduces an interesting and alternative way to design absorbing boundary conditions (ABCs) for quantum wave equations, basically the nonlinear Schrödinger equation. The focus of this book is the application of the phase space filter approach to derive accurate radiation conditions for Schrödinger equations. Researchers who are interested in partial differential equations and mathematical physics might find this book appealing.
An Introduction to Parametric Digital Filters and Oscillators
Author: Mikhail Cherniakov
language: en
Publisher: John Wiley & Sons
Release Date: 2003-07-18
Since the 1960s Digital Signal Processing (DSP) has been one of the most intensive fields of study in electronics. However, little has been produced specifically on linear non-adaptive time-variant digital filters. * The first book to be dedicated to Time-Variant Filtering * Provides a complete introduction to the theory and practice of one of the subclasses of time-varying digital systems, parametric digital filters and oscillators * Presents many examples demonstrating the application of the techniques An indispensable resource for professional engineers, researchers and PhD students involved in digital signal and image processing, as well as postgraduate students on courses in computer, electrical, electronic and similar departments.
Statistical Models and Methods for Financial Markets
Author: Tze Leung Lai
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-07-25
The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005.