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Author Moon, T.K.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1994
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Pattern recognition ♦ Hidden Markov models ♦ Training data ♦ Moon ♦ Testing ♦ Computational complexity ♦ Speech recognition ♦ Intelligent systems ♦ Equations ♦ Convergence
Abstract In many problems it is necessary to recognize patterns of time sequences of feature vectors where the training vectors and the test vectors are not temporally aligned. In this paper the author presents a fuzzy clustering approach to this temporal pattern recognition. Observation classification vectors are embedded into a larger vector that explicitly shows the time dependence. Clustering is done both in this larger space and in the observation space to give "state" and "output" spaces similar to those used in HMM modeling. Recognition is accomplished by finding the best match in state order to the clustering.<<ETX>>
Description Author affiliation: Dept. of Electr. Eng., Utah State Univ., Logan, UT, USA (Moon, T.K.)
ISBN 078031896X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1994-06-26
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 313.53 kB
Page Count 4
Starting Page 432
Ending Page 435


Source: IEEE Xplore Digital Library