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{ "item_title" : "Pattern Recognition and Classification in Time Series Data", "item_author" : [" Eva Volna", "Martin Kotyrba", "Michal Janosek "], "item_description" : "Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/1/52/250/565/1522505652_b.jpg", "price_data" : { "retail_price" : "185.00", "online_price" : "185.00", "our_price" : "185.00", "club_price" : "185.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Pattern Recognition and Classification in Time Series Data|Eva Volna

Pattern Recognition and Classification in Time Series Data

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Overview

Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

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Details

  • ISBN-13: 9781522505655
  • ISBN-10: 1522505652
  • Publisher: Information Science Reference
  • Publish Date: July 2016
  • Dimensions: 10 x 7 x 0.69 inches
  • Shipping Weight: 1.61 pounds
  • Page Count: 296

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