Abstract
In this paper, a transient analysis is performed for a least squares based adaptive algorithm, Euclidean Direction Search algorithm. The transient analysis is characterized by derivations of the energy conservation relation and the learning curve equation. The learning curve equation is particularly important because it describes the learning mechanism of the algorithm without an explicit recursion for the weight vector.
| Original language | English (US) |
|---|---|
| Title of host publication | Conference Record - Asilomar Conference on Signals, Systems and Computers |
| Editors | M.B. Matthews |
| Pages | 1554-1558 |
| Number of pages | 5 |
| Volume | 2 |
| State | Published - 2004 |
| Externally published | Yes |
| Event | Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 7 2004 → Nov 10 2004 |
Other
| Other | Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers |
|---|---|
| Country | United States |
| City | Pacific Grove, CA |
| Period | 11/7/04 → 11/10/04 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Transient analysis of the Euclidean Direction Search (EDS) algorithm. / Zhang, Zhongkai; Bose, Tamal; Gunther, Jacob.
Conference Record - Asilomar Conference on Signals, Systems and Computers. ed. / M.B. Matthews. Vol. 2 2004. p. 1554-1558.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Transient analysis of the Euclidean Direction Search (EDS) algorithm
AU - Zhang, Zhongkai
AU - Bose, Tamal
AU - Gunther, Jacob
PY - 2004
Y1 - 2004
N2 - In this paper, a transient analysis is performed for a least squares based adaptive algorithm, Euclidean Direction Search algorithm. The transient analysis is characterized by derivations of the energy conservation relation and the learning curve equation. The learning curve equation is particularly important because it describes the learning mechanism of the algorithm without an explicit recursion for the weight vector.
AB - In this paper, a transient analysis is performed for a least squares based adaptive algorithm, Euclidean Direction Search algorithm. The transient analysis is characterized by derivations of the energy conservation relation and the learning curve equation. The learning curve equation is particularly important because it describes the learning mechanism of the algorithm without an explicit recursion for the weight vector.
UR - http://www.scopus.com/inward/record.url?scp=21644436367&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=21644436367&partnerID=8YFLogxK
M3 - Conference contribution
VL - 2
SP - 1554
EP - 1558
BT - Conference Record - Asilomar Conference on Signals, Systems and Computers
A2 - Matthews, M.B.
ER -