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Financial Signal Processing and Machine Learning
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processi...
Multiresolution Signal Decomposition
This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decomposition techniquesn Classroom tested textbook clearly describes the commonalities among three key methods-transform coding, and wavelet transformsn Gives comparative performance evaluations of many proposed techniques
A Primer for Financial Engineering
This book bridges the fields of finance, mathematical finance and engineering, and is suitable for engineers and computer scientists who are looking to apply engineering principles to financial markets. The book builds from the fundamentals, with the help of simple examples, clearly explaining the concepts to the level needed by an engineer, while showing their practical significance. Topics covered include an in depth examination of market microstructure and trading, a detailed explanation of High Frequency Trading and the 2010 Flash Crash, risk analysis and management, popular trading strategies and their characteristics, and High Performance DSP and Financial Computing. The book has many ...
Data Hiding Fundamentals and Applications
Multimedia technologies are becoming more sophisticated, enabling the Internet to accommodate a rapidly growing audience with a full range of services and efficient delivery methods. Although the Internet now puts communication, education, commerce and socialization at our finger tips, its rapid growth has raised some weighty security concerns with respect to multimedia content. The owners of this content face enormous challenges in safeguarding their intellectual property, while still exploiting the Internet as an important resource for commerce. Data Hiding Fundamentals and Applications focuses on the theory and state-of-the-art applications of content security and data hiding in digital m...
Subband and Wavelet Transforms
The scientists and engineers of today are relentless in their continuing study and analysis of the world about us from the microcosm to the macrocosm. A central purpose of this study is to gain sufficient scientific information and insight to enable the development of both representative and useful models of the superabundance of physical processes that surround us. The engineers need these models and the associated insight in order to build the information processing systems and control systems that comprise these new and emerging technologies. Much of the early modeling work that has been done on these systems has been based on the linear time-invariant system theory and its extensive use of Fourier transform theory for both continuous and discrete systems and signals. However many of the signals arising in nature and real systems are neither stationary nor linear but tend to be concentrated in both time and frequency. Hence a new methodology is needed to take these factors properly into account.
Financial Signal Processing and Machine Learning
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processi...
NETWORKING 2000. Broadband Communications, High Performance Networking, and Performance of Communication Networks
This was the first conference jointly organized by the IFIP Working Groups 6. 2, 6. 3, and 6. 4. Each of these three Working Groups has its own established series of conferences. Working Group 6. 2 sponsors the Broadband Communications series of conferences (Paris 1995, Montreal 1996, Lisboa 1997, Stuttgart 1998, and Hong-Kong 1999). Working Group 6. 3 sponsors the Performance of Communication Systems series of conferences (Paris 1981, Zürich 1984, Rio de Janeiro 1987, Barcelona 1990, Raleigh 1993, Istanbul 1995, and Lund 1998). Working Group 6. 4 sponsors the High Performance Networking series of conferences (Aaren 1987, Liège 1988, Berlin 1990, Liège 1992, Grenoble 1994, Palma 1995, New...
Digital Image Watermarking
The Book presents an overview of newly developed watermarking techniques in various independent and hybrid domains Covers the basics of digital watermarking, its types, domain in which it is implemented and the application of machine learning algorithms onto digital watermarking Reviews hardware implementation of watermarking Discusses optimization problems and solutions in watermarking with a special focus on bio-inspired algorithms Includes a case study along with its MATLAB code and simulation results
Time-Frequency Analysis Techniques and their Applications
Most of the real-life signals are non-stationary in nature. The examples of such signals include biomedical signals, communication signals, speech, earthquake signals, vibration signals, etc. Time-frequency analysis plays an important role for extracting the meaningful information from these signals. The book presents time-frequency analysis methods together with their various applications. The basic concepts of signals and different ways of representing signals have been provided. The various time-frequency analysis techniques namely, short-time Fourier transform, wavelet transform, quadratic time-frequency transforms, advanced wavelet transforms, and adaptive time-frequency transforms have...
Wavelet Analysis and Applications
Wavelet analysis has been one of the major research directions in science in the last decade. More and more mathematicians and scientists join this exciting research area. Certainly, wavelet analysis has had a great impact in areas such as approximation theory, harmonic analysis, and scientific computation. More importantly, wavelet analysis has shown great potential in applications to information technology such as signal processing, image processing, and computer graphics. Chinahas played a significant role in this development of wavelet analysis as evidenced by many fruitful theoretical results and practical applications. A conference on wavelet analysis and its applications was organized...
