NDLI: Fast K-dimensional tree algorithms for nearest neighbor search with application to vector quantization encoding

Content Provider	IEEE Xplore Digital Library
Author	Ramasubramanian, V. Paliwal, K.K.
Copyright Year	1991
Abstract	Fast search algorithms are proposed and studied for vector quantization encoding using the K-dimensional (K-d) tree structure. Here, the emphasis is on the optimal design of the K-d tree for efficient nearest neighbor search in multidimensional space under a bucket-Voronoi intersection search framework. Efficient optimization criteria and procedures are proposed for designing the K-d tree, for the case when the test data distribution is available (as in vector quantization application in the form of training data) as well as for the case when the test data distribution is not available and only the Voronoi intersection information is to be used. The criteria and bucket-Voronoi intersection search procedure are studied in the context of vector quantization encoding of speech waveform. They are empirically observed to achieve constant search complexity for O(log N) tree depths and are found to be more efficient in reducing the search complexity. A geometric interpretation is given for the maximum product criterion, explaining reasons for its inefficiency with respect to the optimization criteria.<>
Sponsorship	IEEE Signal Processing Society
Starting Page	518
Ending Page	531
Page Count	14
File Size	1278734
File Format	PDF
ISSN	1053587X
Volume Number	40
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nearest neighbor searches Encoding Vector quantization Multidimensional systems Testing Tree data structures Design optimization Data compression Training data Speech
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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