Автор: Buttazzo Название: Hard Real-Time Computing Systems ISBN: 0387231374 ISBN-13(EAN): 9780387231372 Издательство: Springer Рейтинг: Цена: 11173.00 р. Наличие на складе: Поставка под заказ.
Описание: Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications is a basic treatise on real-time computing, with particular emphasis on predictable scheduling algorithms. It introduces the fundamental concepts of real-time computing, illustrates the most significant results in the field, and provides the essential methodologies for designing predictable computing systems which can be used to support critical control applications.This volume serves as a textbook for advanced level courses on the topic. Each chapter provides basic concepts, which are followed by algorithms that are illustrated with concrete examples, figures and tables. Exercises are included with each chapter and solutions are given at the end of the book. The book also provides an excellent reference for those interested in real-time computing for designing and/or developing predictable control applications.
Автор: Tao Li; Mitsunori Ogihara; George Tzanetakis Название: Music Data Mining ISBN: 1439835527 ISBN-13(EAN): 9781439835524 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to successfully employ data mining techniques for the purpose of music processing.
The book first covers music data mining tasks and algorithms and audio feature extraction, providing a framework for subsequent chapters. With a focus on data classification, it then describes a computational approach inspired by human auditory perception and examines instrument recognition, the effects of music on moods and emotions, and the connections between power laws and music aesthetics. Given the importance of social aspects in understanding music, the text addresses the use of the Web and peer-to-peer networks for both music data mining and evaluating music mining tasks and algorithms. It also discusses indexing with tags and explains how data can be collected using online human computation games. The final chapters offer a balanced exploration of hit song science as well as a look at symbolic musicology and data mining.
The multifaceted nature of music information often requires algorithms and systems using sophisticated signal processing and machine learning techniques to better extract useful information. An excellent introduction to the field, this volume presents state-of-the-art techniques in music data mining and information retrieval to create novel ways of interacting with large music collections.
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