Name
Title | ||
|---|---|---|
Convergence analysis of deterministic discrete time system of a unified self-stabilizing algorithm for PCA and MCA. |
Abstract | ||
|---|---|---|
Unified algorithms for principal and minor components analysis can be used to extract principal components and if altered simply by the sign, it can also serve as a minor component extractor. Obviously, the convergence of these algorithms is an essential issue in practical applications. This paper studies the convergence of a unified PCA and MCA algorithm via a corresponding deterministic discrete-time (DDT) system and some sufficient conditions to guarantee convergence are obtained. Simulations are carried out to further illustrate the theoretical results achieved. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.neunet.2012.08.016 | Neural Networks |
Keywords | Field | DocType |
corresponding deterministic discrete-time,essential issue,mca algorithm,unified self-stabilizing algorithm,deterministic discrete time system,minor components analysis,paper study,principal component,convergence analysis,minor component extractor,sufficient condition,unified algorithm,practical application,neural networks,feature extraction | Convergence (routing),Discrete time system,Computer science,Algorithm,Feature extraction,Artificial intelligence,Extractor,Artificial neural network,Machine learning,Principal component analysis | Journal |
Volume | Issue | ISSN |
36 | 1 | 1879-2782 |
Citations | PageRank | References |
6 | 0.40 | 29 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangyu Kong | 1 | 65 | 15.61 |
| Qiusheng An | 2 | 12 | 2.92 |
| Hong-Guang Ma | 3 | 60 | 8.41 |
| Chongzhao Han | 4 | 446 | 71.68 |
| Qi Zhang | 5 | 6 | 0.40 |