Pattern Matching Algorithms (94 results)

hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

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Taschenbuch. Condition: Neu. Neuware -Analysis of Algorithms for Graph Pattern Matching Problems is designed to serve as a reference book for researchers. This book is primarily deals with the introductory concept of graph, graph pattern matching, graph isomorphism and their applications. A decision tree approach is proposed to solve graph pattern matching problem. This book also covers different algorithms for pattern matching problem. Complexity analysis and experimental result are also discussed in this book. Salient Features: Introductory concept of graph pattern matching and graph isomorphism Different algorithms for graph pattern matching problem Comparative analysis of algorithms Applications of graph pattern matching problemBooks on Demand GmbH, Überseering 33, 22297 Hamburg 72 pp. Englisch.

Condition: New.

Paperback. Condition: Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. The Science of Pattern Matching in Learning Algorithms presents a comprehensive guide to understanding the science behind pattern matching in learning algorithms. By exploring the latest research on cognitive psychology and artificial intelligence, readers will gain a deeper understanding of how pattern matching works, and how to apply this knowledge to improve learning performance. This book presents a range of engaging examples and case studies, illustrating the ways in which pattern matching intersects with learning algorithms in real-world contexts. Through a series of practical exercises and thought experiments, readers will learn to develop a more nuanced understanding of pattern matching, and how to apply this knowledge to improve their own learning performance and cognitive abilities. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condition: New. Dust Jacket Condition: no dj. First. The Science of Pattern Matching in Learning Algorithms presents a groundbreaking approach to understanding the neural mechanisms underlying pattern matching in learning algorithms. By examining the complex interplay between pattern recognition, memory, and decision-making, this book reveals the critical role that pattern matching plays in shaping our learning outcomes. Through a series of engaging case studies and insightful analyses, The Science of Pattern Matching in Learning Algorithms provides readers with a deeper understanding of the neural mechanisms underlying pattern matching. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

orig.cloth. Condition: Minor rubbing. VG. 24x16cm, (12),377 pp Contains 11 papers. Includes: M. Crochemore "Off-Line Serial Exact String Searching"; Z. Galil & I. Yudkiewicz "Off-Line Parallel Exact String Searching"; A. Apostolico "On-Line String Searching"; D. Hirschberg " Serial Computations of Levenshtein Distances"; A. Apostolico & M.J. Atallah "Parallel Computations of Levenshtein Distances"; G.M. Landau & U. Vishkin "Approximate String Searching"; R. Giancarlo "Dynamic Programming: Special Cases"; M. Li & T. Jiang "Shortest Common Superstrings"; A. Amir & M, Farach "Two Dimensional Matching"; R. Giancardo & R. Grossi "Suffix Tree Data Structures for Matrices"; K. Zhang & S. Shasha "Tree Pattern Matching".

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In part 2, fast motion estimation algorithm with name Fast Multigrid Pattern Search (FMPS) for H.264 is proposed. The proposed method showed that it works about 4 times faster. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms (up to 3.75%) so it requires further investigation. Also, part 2 deals with the fast motion estimation algorithms for interframe encoding in the video data H.26 /HEVC standard. A new adaptive algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. The algorithm is called fast test zone search algorithm and includes the traditional test zone search algorithm (TZS) and the hierarchical search MP (Hierarchical Search or Mean Pyramid). The considered and proposed motion estimation algorithms have been tested in several video sequences using Microsoft Visual Studio software. The terms for algorithms evaluating were: the video sequence quality criterion (by PSNR), bitrate and encoding time. The proposed method showed that it works about 4 times faster. The average loss of the RD curve value (PSNR versus bitrate) is up to 4% in all.