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.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Maße
Höhe: 260 mm
Breite: 183 mm
Dicke: 21 mm
Gewicht
ISBN-13
978-1-5225-0565-5 (9781522505655)
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Schweitzer Klassifikation
Eva Volna, University of Ostrava, Czech Republic.
Martin Kotyrba, University of Ostrava, Czech Republic.
Michal Janosek, University of Ostrava, Czech Republic.