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.
Автор: Goodwin, Graham Название: Adaptive Filtering Prediction and Control ISBN: 0486469328 ISBN-13(EAN): 9780486469324 Издательство: Dover Рейтинг: Цена: 3468.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Oxford Encyclopedia of Theatre and Performance provides comprehensive, authoritative, and up-to-date information about all aspects of the history and practice of theatre and performance - including dance, opera, radio, film, television, and popular performance, such as carnivals, circus, and public executions. It is also available as an e-reference text from Oxford`s Digital Reference Shelf.
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.
Автор: Jazwinski, Andrew Название: Stochastic Processes and Filtering Theory ISBN: 0486462749 ISBN-13(EAN): 9780486462745 Издательство: Dover Рейтинг: Цена: 3723.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Strategy - Application - Innovation
Human Resources Management, 3 rd edition is an all-inclusive resource packed full of Australian examples, quality pedagogical features and cutting edge theories. It provides an excellent balance of practical teaching and the underlying theory of HRM which helps students understand what HR actually is, rather than just how to practice it.
The text facilitates the development of critical and innovative thinking, allowing readers to make Co-adaptive Human Resource Management (CHRM) decisions in the light of the diverse features of any given business and its operating environment.
Hartel and Fujimoto underscore HRM as a core aspect of management and a function which creates sustainable value for organisations and society, making it essential reading for all students, academics and practitioners of HRM.
Описание: Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
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.
