Processing Random Data
Processing Random Data

Author: Robert V. Edwards

Publisher: World Scientific

Published: 2006

Total Pages: 156

ISBN-13: 9812568344

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Two features of Processing Random Data differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques. The book is useful for dealing with situations where there is a model relating to the input and output of a process, but with a random component, which could be noise in the system or the process itself could be random, like turbulence. Parameter estimation techniques are shown for many different types of statistical models, including joint Gaussian. The Cramer-Rao bounds are described as useful estimates of reproducibility errors.Finally, using an example with a random sampling of turbulent flows that can occur when using laser anemometry the book also explains the use of conditional probabilities.

Processing Random Data: Statistics For Engineers And Scientists
Processing Random Data: Statistics For Engineers And Scientists

Author: Robert V Edwards

Publisher: World Scientific Publishing Company

Published: 2006-07-03

Total Pages: 152

ISBN-13: 9813106727

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Two features of Processing Random Data differentiate it from other similar books: the focus on computing the reproducibility error for statistical measurements, and its comprehensive coverage of Maximum Likelihood parameter estimation techniques. The book is useful for dealing with situations where there is a model relating to the input and output of a process, but with a random component, which could be noise in the system or the process itself could be random, like turbulence. Parameter estimation techniques are shown for many different types of statistical models, including joint Gaussian. The Cramer-Rao bounds are described as useful estimates of reproducibility errors.Finally, using an example with a random sampling of turbulent flows that can occur when using laser anemometry the book also explains the use of conditional probabilities.

Digital Processing of Random Signals
Digital Processing of Random Signals

Author: Boaz Porat

Publisher: Courier Dover Publications

Published: 2008-02-29

Total Pages: 468

ISBN-13: 0486462986

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This excellent advanced text rigorously covers several topics. Geared toward students of electrical engineering, its material is sufficiently general to be applicable to other engineering fields. 1994 edition.

Aerospace Instrumentation
Aerospace Instrumentation

Author: M. A. Perry

Publisher: Elsevier

Published: 2015-05-18

Total Pages: 297

ISBN-13: 1483223396

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Aerospace Instrumentation, Volume 4 is a collection of papers presented at the Fourth International Aerospace Instrumentation Symposium, held at the College of Aeronautics, Cranfield. Co-sponsored by the Instrument Society of America, the symposium covers most aspects of aerospace instrumentation. This book is composed of 14 chapters and begins with a description of strain gauge transducers, an introduction to noise, filtering, and random function, as well as the data analysis facility designed to satisfy the needs in the fields of fundamental research and major power plant design and commissioning. A chapter examines equipment for the analysis of random processes for low frequence purposes. Other chapters explore the measurement and analysis of rotor blade airloads, the application of digital computer to instrumentation systems, the features of an altitude test facility, and the trade-offs existing between analogue and digital filtering techniques. The last chapters are devoted to test methods for aircraft performance, stability, and control characteristics determination in non-steady flight. These chapters also treat the operational experience of the B-70 flight test data system. This book will prove useful to aerospace scientists, engineers and research workers.

Random Processes for Image and Signal Processing
Random Processes for Image and Signal Processing

Author: Edward R. Dougherty

Publisher: SPIE-International Society for Optical Engineering

Published: 1999

Total Pages: 624

ISBN-13:

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Part of the SPIE/IEEE Series on Imaging Science and Engineering. This book provides a framework for understanding the ensemble of temporal, spatial, and higher-dimensional processes in science and engineering that vary randomly in observations. Suitable as a text for undergraduate and graduate students with a strong background in probability and as a graduate text in image processing courses.

Learning Processing
Learning Processing

Author: Daniel Shiffman

Publisher: Newnes

Published: 2015-09-09

Total Pages: 566

ISBN-13: 0123947928

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Learning Processing, Second Edition, is a friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages. Requiring no previous experience, this book is for the true programming beginner. It teaches the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. Step-by-step examples, thorough explanations, hands-on exercises, and sample code, supports your learning curve.A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. The book has been developed with a supportive learning experience at its core. From algorithms and data mining to rendering and debugging, it teaches object-oriented programming from the ground up within the fascinating context of interactive visual media.This book is ideal for graphic designers and visual artists without programming background who want to learn programming. It will also appeal to students taking college and graduate courses in interactive media or visual computing, and for self-study. - A friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages - No previous experience required—this book is for the true programming beginner! - Step-by-step examples, thorough explanations, hands-on exercises, and sample code supports your learning curve

Random Data
Random Data

Author: Julius S. Bendat

Publisher: Wiley-Interscience

Published: 2000-02-14

Total Pages: 634

ISBN-13:

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The classic reference on the theory and application of random data analysis-now expanded and revised. This eagerly awaited new edition of the bestselling random data analysis book continues to provide first-rate, practical tools for scientists and engineers who investigate dynamic data as well as those who use statistical methods to solve engineering problems. It is fully updated, covering new procedures developed since 1986 and extending the discussion to a remarkably broad range of applied fields, from aerospace and automotive industries to biomedical research. Comprehensive and self-contained, this new edition also greatly expands coverage of the theory, including derivations of key relationships in probability and random process theory not usually found in books of this kind. Special features of Random Data: Analysis and Measurement Procedures, Third Edition include: * Basic probability functions for level crossings and peak values of random data * Complete derivations of both old and new practical formulas for statistical error analysis of computed estimates * The latest methods for data acquisition and processing as well as nonstationary data analysis * Additional techniques on digital data analysis procedures * New material on the analysis of multiple-input/multiple-output linear systems * Numerous new examples and problem sets * Hundreds of updated illustrations and references *An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Deep Learning for Coders with fastai and PyTorch
Deep Learning for Coders with fastai and PyTorch

Author: Jeremy Howard

Publisher: O'Reilly Media

Published: 2020-06-29

Total Pages: 624

ISBN-13: 1492045497

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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Parallel and Distributed Processing and Applications
Parallel and Distributed Processing and Applications

Author: Ivan Stojmenovic

Publisher: Springer Science & Business Media

Published: 2007-08-22

Total Pages: 1013

ISBN-13: 3540747427

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This book constitutes the refereed proceedings of the 5th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2007, held in Niagara Falls, Canada, in August 2007. The 83 revised full papers presented together with three keynote are cover algorithms and applications, architectures and systems, datamining and databases, fault tolerance and security, middleware and cooperative computing, networks, as well as software and languages.

Neural Information Processing
Neural Information Processing

Author: Chu Kiong Loo

Publisher: Springer

Published: 2014-10-20

Total Pages: 666

ISBN-13: 3319126377

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The three volume set LNCS 8834, LNCS 8835, and LNCS 8836 constitutes the proceedings of the 21st International Conference on Neural Information Processing, ICONIP 2014, held in Kuching, Malaysia, in November 2014. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The selected papers cover major topics of theoretical research, empirical study, and applications of neural information processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory and design, applications, kernel and statistical methods, evolutionary computation and hybrid intelligent systems, signal and image processing, and special sessions intelligent systems for supporting decision, making processes, theories and applications, cognitive robotics, and learning systems for social network and web mining.