The systolic architecture for hierarchical clustering.

Bibliographic Details
Main Author: Ku, Long-Chian
Other Authors: Friesen, Donald K. (degree committee member.), Morgan, Stephen M. (degree committee member.), Noe, Philip S. (degree committee member.)
Format: Thesis Book
Language:English
Published: 1984.
Subjects:
Online Access:Link to ProQuest Copy
Link to OAKTrust copy

MARC

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099 |a 1984  |a Dissertation  |a K95 
100 1 |a Ku, Long-Chian 
245 1 4 |a The systolic architecture for hierarchical clustering. 
264 1 |c 1984. 
300 |a ix, 82 leaves :  |b illustrations ;  |c 29 cm 
336 |a text  |b txt  |2 rdacontent 
337 |a unmediated  |b n  |2 rdamedia 
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500 |a "Major subject: Computer Science." 
500 |a Typescript (photocopy). 
500 |a Vita. 
502 |b Ph. D. in Philosophy  |c Texas A & M University  |d 1984 
504 |a Includes bibliographical references (leaves 76-81). 
520 3 |a Several hierarchical clustering methods (including single-linkage, complete-linkage, centroid, and absolute overlap methods) are reviewed. The absolute overlap clustering method is selected for the design of systolic architecture mainly due to its simplicity. Two versions of systolic architectures for the absolute overlap hierarchical clustering algorithm are proposed. A one dimensional version that leads to the development of a two dimensional version which fully takes advantage of the underlying data structure of the problems. The two dimensional systolic architecture can achieve a time complexity of O(m + n) in comparison to the conventional computer implementation of a time complexity of O(m('2)*n). 
650 0 |a Cluster analysis. 
650 0 |a Computer architecture. 
650 4 |a Computer Science 
655 7 |a Academic theses  |2 lcgft 
700 1 |a Drew, Dan D.,  |e degree supervisor. 
700 1 |a Friesen, Donald K.,  |e degree committee member. 
700 1 |a Morgan, Stephen M.,  |e degree committee member. 
700 1 |a Noe, Philip S.,  |e degree committee member. 
710 2 |a Texas A & M University,  |e degree granting institution. 
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