Abstract
The convergence of Oja+'s MCA learning algorithm was proven in past by using a deterministic continuous-time dynamical system with, restrictive condition that the learning rate must converge to zero. This paper gives a new proof for the convergence of the Oja+'s MCA algorithm via a corresponding deterministic discrete-time (DDT) dynamical system. This approach allows the learning rate to be some constant. In this paper, the fixed points of the DDT system are determined and an invariant set is obtained. Based on the invariant set, the convergence is proven. © Springer-Verlag 2004.
Cite
CITATION STYLE
Lv, J., Ye, M., & Yi, Z. (2004). Convergence analysis for Oja+ MCA learning algorithm. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3173, 810–814. https://doi.org/10.1007/978-3-540-28647-9_133
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