Автор: Anderson, Brian Название: Optimal Filtering ISBN: 0486439380 ISBN-13(EAN): 9780486439389 Издательство: Dover Рейтинг: Цена: 3344.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: THE TWENTY ETUDES FOR PIANO were composed during the years from 1991 to 2012. Their final configuration into Book 1 and Book 2 was determined by the music itself in the course of its composition.
Book 1 (Etudes 1-10) had a twin objective - to explore a variety of tempi, textures and piano techniques. At the same time it was meant to serve as a pedagogical tool by which I would improve my piano playing. In these two ways, Book 1 succeeded very well. I learned a great deal about the piano and in the course of learning the music, I became a better player.
New projects came along and interrupted the work on the Etudes for several years. Perhaps for that reason, when I took up work with the Etudes again I found the music was following a new path. Though I had settled questions of piano technique for myself in Book 1, the music in Book 2 quickly began to suggest a series of new adventures in harmony and structure.
In this way, Books 1 and 2, taken together, suggest a real trajectory that includes a broad range of music and technical ideas.
In the end, the Etudes are meant to be appreciated not only by the general listener, but especially by those who have the ability and patience to learn, play and perform the music themselves.
Автор: Koushik Ghosh, Souvik Bhattacharyya Название: Noise Filtering for Big Data Analytics ISBN: 3110697092 ISBN-13(EAN): 9783110697094 Издательство: Walter de Gruyter Рейтинг: Цена: 26024.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model.
Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information.
This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.
Описание: Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
Описание: Bayesian Bounds provides a collection of the important papers dealing with the theory and application of Bayesian bounds. The book will be useful to both engineers and statisticians whether they are practicioners or theorists. The organization of the book and selection criteria is covered in the preface. Each part is introduced with the contributions of each selected paper and their interrelationship. Part 1contains a short history of Reverend Thomas Bayes and his classic paper that established the field. Part 2 contains the original derivation of the Bayesian Cramer-Rao bound and a simple derivation of the multiple parameter Bayesian CRB. Part 3 discusses global Bayesian bounds to provide broad coverage of this important area. Part 4 considers the case in which some of the parameters are deterministic and some are random. Hybrid Bayesian bounds are derived, as they are particularly important in the study of model mismatch problems. Part 5 considers generalized Cramer-Rao bounds. Part 6 discusses nonlinear stochastic dynamic systems. This type of system is a major component of most radar, sonar, and navigation systems. They are also encountered in nonlinear filtering problems. Applications of various Bayesian bounds to static parameter estimation problems are covered in Part 7 and to dynamic systems in Part 8. The book concludes with papers from the statistics literature that focus on Bayesian bounds in various models in Part 9.
Описание: This is the first book to combine speckle imaging and video filtering and tracking, and their applications. It provides different levels of material to researchers interested in developing imaging and video systems with better quality by limiting the corruption of speckle noise in their systems.
Автор: Koushik Ghosh, Souvik Bhattacharyya Название: Noise Filtering for Big Data Analytics ISBN: 3110697262 ISBN-13(EAN): 9783110697261 Издательство: Walter de Gruyter Рейтинг: Цена: 25848.00 р. Наличие на складе: Нет в наличии.
Описание:
This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.
Автор: Dimitris G. Manolakis Название: Statisical and Adaptive Signal Processing ISBN: 1580536107 ISBN-13(EAN): 9781580536103 Издательство: Artech House Рейтинг: Цена: 29117.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Originally published by McGraw-Hill and now reissued by Artech House, this definitive volume offers a unified, comprehensive and practical treatment of statistical and adaptive signal processing. Written by leading experts in industry and academia, the book covers the most important aspects of the subject, such as spectral estimation, signal modeling, adaptive filtering, and array processing.
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