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An Introduction to Sparse Stochastic Processes
A detailed guide to sparsity, providing a description of their transform-domain statistics and applying the models to practical algorithms.
An Introduction to Sparse Stochastic Processes
Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistics.
Contesting the Iranian Revolution
Examines the last forty years of Iranian and Middle-Eastern history through the prism of the Green Uprisings of 2009.
The Atlas of Economic Complexity
Maps capture data expressing the economic complexity of countries from Albania to Zimbabwe, offering current economic measures and as well as a guide to achieving prosperity Why do some countries grow and others do not? The authors of The Atlas of Economic Complexity offer readers an explanation based on "Economic Complexity," a measure of a society's productive knowledge. Prosperous societies are those that have the knowledge to make a larger variety of more complex products. The Atlas of Economic Complexity attempts to measure the amount of productive knowledge countries hold and how they can move to accumulate more of it by making more complex products. Through the graphical representatio...
Why Information Grows
In Why Information Grows, rising star César Hidalgo offers a radical interpretation of global economics While economists often turn to measures like GDP or per-capita income, César Hidalgo turns to information theory to explain the success or failure of a country's economic performance. Through a radical rethinking of what the economy is, Hidalgo shows that natural constraints in our ability to accumulate knowledge, knowhow and information explain the evolution of social and economic complexity. This is a rare tour de force, linking economics, sociology, physics, biology and information theory, to explain the evolution of social and economic systems as a consequence of the physical embodiment of information in a world where knowledge is quite literally power. César Hidalgo leads the Macro Connections group at the MIT Media Lab. A trained statistical physicist and an expert on Networks and Complex Systems, he also has extensive experience in the field of economic development and has pioneered research on how big data impacts economic decision-making.
Spectral Analysis for Univariate Time Series
Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.
Numerical Methods and Optimization in Finance
Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using...
Global Electronic Commerce
Provides an understanding of the technologies of electronic commerce. The text does not concentrate solely on the Internet but suggests that the Internet is only a bridge technology. Each chapter contains an overview of a theory or practice followed by one or more business case studies.
