Masters Theses
Abstract
"This thesis is on a research problem to identify and classify Gaussian processes. It started with the detection of landmines and moved onto a generalization of the classification problem. The main part of the thesis deals with dimensionality reduction of the large dimension AR spectrums obtained for the landmines. It was demonstrated by earlier research work that many of the algorithms that work well for small dimension feature vectors are unable to duplicate the same classification results for the large dimension vectors. The algorithms for reduction of the feature vector dimension studied here are the Fisher's linear discriminant analysis and the Fisher's multiple discriminant analysis"--Abstract, page iii.
Advisor(s)
Stuller, John A.
Committee Member(s)
Cunningham, David R.
Dagli, Cihan H., 1949-
Department(s)
Electrical and Computer Engineering
Degree Name
M.S. in Electrical Engineering
Publisher
University of Missouri--Rolla
Publication Date
Spring 2000
Pagination
ix, 60 pages
Note about bibliography
Includes bibliographical references (page 59).
Rights
© 2000 Akshaya Shankar Puranik, All rights reserved.
Document Type
Thesis - Restricted Access
File Type
text
Language
English
Thesis Number
T 7713
Print OCLC #
43931881
Electronic OCLC #
1101968338
Link to Catalog Record
Electronic access to the full-text of this document is restricted to Missouri S&T users. Otherwise, request this publication directly from Missouri S&T Library or contact your local library.
http://merlin.lib.umsystem.edu/record=b4414633~S5Recommended Citation
Puranik, Akshaya Shankar, "A study of classification techniques with applications in landmine detection" (2000). Masters Theses. 1898.
https://scholarsmine.mst.edu/masters_theses/1898
Share My Thesis If you are the author of this work and would like to grant permission to make it openly accessible to all, please click the button above.