Systemic Corruption: Constitutional Ideas for an Anti-Oligarchic Republic, Vergara Camila
Автор: Vergara Angela Название: Copper Workers, International Business, and Domestic Politics in Cold War Chile ISBN: 0271033355 ISBN-13(EAN): 9780271033358 Издательство: NBN International Рейтинг: Цена: 42170.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Traces the history of the labor movement in Chile through the experiences of copper miners employed by the Anaconda Copper Company from 1945 to 1990. Covers the economic, political, and social history of the 45-year period when the Cold War dominated Chilean politics.
Автор: Vergara Camus Leandro Название: Land and Freedom ISBN: 1780327420 ISBN-13(EAN): 9781780327426 Издательство: Little Brown Рейтинг: Цена: 24280.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The only comparative analysis of the Zapatistas and the MST.
Автор: Evans G. Edward, Alire Camila Название: Management Basics for Information Professionals ISBN: 1555709095 ISBN-13(EAN): 9781555709099 Издательство: Неизвестно Цена: 68970.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Vergara Walter, Deeb Alejandro, Toba Natsuko Название: Wind Energy in Colombia: A Framework for Market Entry ISBN: 0821385046 ISBN-13(EAN): 9780821385043 Издательство: Mare Nostrum (Eurospan) Цена: 20900.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Colombia has vast wind potential, in fact one of the best in South America. However, currently it is not seen as a viable option by itself. This report gives a set of policy options for the decision makers in Colombia and other countries in the region to better promote the use of wind power.
Автор: Addisson Salazar, Luis Vergara Название: Independent Component Analysis (ICA): Algorithms, Applications and Ambiguities ISBN: 1536139947 ISBN-13(EAN): 9781536139945 Издательство: Nova Science Рейтинг: Цена: 257650.00 T Наличие на складе: Невозможна поставка. Описание: Modern treatment of data requires powerful tools that allow the possible valuable contents of that data to be thoroughly understood and exploited. From the plethora of techniques proposed to achieve those objectives, the independent component analysis (ICA) has emerged as a flexible and efficient approach to model and characterize arbitrary data densities. Considering adequate data preprocessing, ICA can be implemented for any kind of data including imaging; biomedical signals; telecommunication data; and web data. In this framework, this book embraces a significant vision of ICA that presents innovative theoretical and practical approaches. ICA has been increasingly studied as a suitable method for many applications where available data describe complex geometries. Thus, this book aims to be an updated and advanced source of knowledge to solve real-world problems efficiently based on ICA. In contrast to classical time and frequency domain filtering, ICA has been proposed as a statistical filtering tool considering the observed data as mixtures of hidden non-Gaussian distributions called sources. Those sources extracted by ICA can be related with meaningful information about the origin of the data and for data detection/classification. Therefore, the successful of ICA has been widely demonstrated in challenging blind source separation (BSS), feature extraction, and pattern recognition tasks. The suitability of ICA for a given problem of data analysis can be posed from different perspectives considering the physical interpretation of the phenomenon under analysis: (i) Estimation of the probability density of multivariate data without physical meaning; (ii) learning of some bases (usually called activation functions), which are more or less connected to the actual behaviors that are implicit in the physical phenomenon; and (iii) to identify where sources are originated and how they mix before arriving to the sensors to provide a physical explanation of the linear mixture model. In any case, even though the complexity of the problem constrains a physical interpretation, ICA can be used as a general-purpose data mining technique. The chapters that compose this book are written by premier researchers that present enlightening discussions, convincing demonstrations, and guidelines for future directions of research. The contents of this book span biomedical signal processing, dynamic modeling, next generation wireless communication, and sound and ultrasound signal processing. It also includes comprehensive works based on the related ICA techniques known as bounded component analysis (BCA) and non-negative matrix factorization (NMF).
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