Abstract/Details

A PARTITIONED DATA COMPRESSION ALGORITHM

KURIEN, THOMAS. 
 University of Connecticut ProQuest Dissertations Publishing,  1983. 8319202.

Abstract (summary)

This thesis introduces a new approach to the design of estimation algorithms. It is applicable to systems which have a special structure and the measurements involve only subsets of the total state vector.

The approach used is to partition the system into subsystems, each containing subsets of the state associated with a particular measurement type. Reduced-order filters are designed for each of these subsystems. A separate full-order filter interacts with these filters to ensure that they maintain close to unbiased (state and covariance) estimates. This full-order filter, in turn, receives compressed information from the reduced-order filters. The combination of the full-order filter and reduced-order filters has a smaller computational requirement compared to that of the optimal filter. In fact, a systematic design approach is provided wherein a trade-off between accuracy and computational requirements can be made. Computer simulation of the algorithm for typical systems has verified the predicted performance of the algorithms.

The design approach introduced in this thesis also provides a hierarchical structure in the estimation process whereby information is assimilated at different rates at different levels. As such the algorithm provides valuable insight for the design of multi-level and multi-rate estimation algorithms for systems of large dimension.

Indexing (details)


Subject
Electrical engineering
Classification
0544: Electrical engineering
Identifier / keyword
Applied sciences
Title
A PARTITIONED DATA COMPRESSION ALGORITHM
Author
KURIEN, THOMAS
Number of pages
167
Degree date
1983
School code
0056
Source
DAI-B 44/04, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
979-8-204-55788-8
University/institution
University of Connecticut
University location
United States -- Connecticut
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
8319202
ProQuest document ID
303265149
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/303265149