Description: Markov Models for Pattern Recognition : From Theory to Applications, Paperback by Fink, Gernot A., ISBN 1447171330, ISBN-13 9781447171331, Like New Used, Free shipping in the US This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.
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Book Title: Markov Models for Pattern Recognition : From Theory to Applicatio
Number of Pages: Xiii, 276 Pages
Publication Name: Markov Models for Pattern Recognition : from Theory to Applications
Language: English
Publisher: Springer London, The Limited
Item Height: 0.6 in
Publication Year: 2016
Subject: Signals & Signal Processing, Probability & Statistics / Stochastic Processes, Intelligence (Ai) & Semantics, Statistics, Speech & Audio Processing, Computer Vision & Pattern Recognition
Type: Textbook
Item Weight: 157.1 Oz
Subject Area: Mathematics, Computers, Technology & Engineering, Business & Economics
Item Length: 9.2 in
Author: Gernot A. Fink
Series: Advances in Computer Vision and Pattern Recognition Ser.
Item Width: 6.1 in
Format: Trade Paperback
