Name
Abstract | ||
|---|---|---|
In this paper we propose a procedure for recursive identification of discrete time PieceWise Affine (PWA) hybrid systems. The PWA identification problem involves the estimation of both the parameters of affine submodels and the partition of the PWA map from data. In this paper the submodel parameters estimation problem is solved via recursive k-plane clustering algorithm and the problem of region estimation is performed by incremental proximal support vector machine. Also, the effect of mode switching on the estimated parameters convergence is investigated. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICARCV.2006.345421 | ICARCV |
Keywords | Field | DocType |
continuous systems,discrete time systems,pattern classification,pattern clustering,recursive estimation,support vector machines,discrete time systems,incremental proximal support vector machine,mode switching,parameter estimation,pattern classification,piecewise affine hybrid systems,recursive identification,recursive k-plane clustering algorithm,region estimation,Classification,Clustering,Hybrid systems,Piecewise affine systems,Recursive Identification | Affine transformation,Mathematical optimization,Affine combination,Computer science,Control theory,Algorithm,Discrete time and continuous time,Estimation theory,Cluster analysis,Hybrid system,Piecewise,Parameter identification problem | Conference |
ISSN | Citations | PageRank |
2474-2953 | 2 | 0.38 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Tabatabaci-pour | 1 | 2 | 0.38 |
| M. Gholami | 2 | 2 | 0.38 |
| H. R. Shaker | 3 | 3 | 0.74 |
| B. Moshiri | 4 | 57 | 7.85 |