This book offers a user friendly, hands-on, and systematic introduction to applied and computational harmonic analysis: to Fourier analysis, signal processing and wavelets; and to their interplay and applications. The...
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ISBN:
(数字)9783030029401
ISBN:
(纸本)9783030029395
This book offers a user friendly, hands-on, and systematic introduction to applied and computational harmonic analysis: to Fourier analysis, signal processing and wavelets; and to their interplay and applications. The approach is novel, and the book can be used in undergraduate courses, for example, following a first course in linear algebra, but is also suitable for use in graduate level courses. The book will benefit anyone with a basic background in linear algebra. It defines fundamental concepts in signal processing and wavelet theory, assuming only a familiarity with elementary linear algebra. No background in signal processing is needed. Additionally, the book demonstrates in detail why linear algebra is often the best way to go. Those with only a signal processing background are also introduced to the world of linear algebra, although a full course is *** book comes in two versions: one based on MATLAB, and one on Python, demonstrating the feasibility and applications of both approaches. Most of the code is available interactively. The applications mainly involve sound and images. The book also includes a rich set of exercises, many of which are of a computational nature.
Significant strategic investments are quickly realizing a pervasive computational infrastructure that integrates computers, networks, data archives, instruments, observatories, and embedded sensors and actuators. This...
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ISBN:
(纸本)9781605585789
Significant strategic investments are quickly realizing a pervasive computational infrastructure that integrates computers, networks, data archives, instruments, observatories, and embedded sensors and actuators. This in turn has the potential for enabling new paradigms and practices in computational science and engineering those that symbiotically and opportunistically combine computations, experiments, observations, and real-time information. However the ability of scientists to realize this potential is being severely hampered primarily due to the increased complexity and dynamism of the applications and the computing infrastructure. Autonomic computing has the potential to fundamentally address these challenges. In this talk, I will motivate autonomics for computational science and engineering. I will then describe research efforts at TASSL, Rutgers University as part of the NSF Center for Autonomic Computing aimed at enabling autonomic scientific and engineering applications that can address the challenges of (and benefit from) pervasive computational ecosystems.
This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regress...
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ISBN:
(数字)9783319283166
ISBN:
(纸本)9783319283166
This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.
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