Separable Recursive Training Algorithms with Switching Module

Asirvadam , Vijanth Sagayan (2009) Separable Recursive Training Algorithms with Switching Module. In: Lecture Notes in Computer Science. Springer. ISBN 364210682X

Full text not available from this repository.
Official URL:


A novel hybrid or separable recursive training strategies are de rived for the training of feedforward neural networks which incoporates a switching module. This new technique for updating weights combines non linear recursive training algorithms for the optimization of nonlinear weights with recursive least square type algorithms for the training of linear weights in one integrated routine. The proposed new variant of hybrid weight update includes switching mechanism based on the condition of input data to the system (correlated or noncorrelated). Simulation results demonstrate the im provement of the new proposed switching mode training scheme.

Item Type: Book Section
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE: Departments > Electrical & Electronic Engineering
Depositing User: Dr Vijanth Sagayan Asirvadam
Date Deposited: 04 Jan 2011 00:39
Last Modified: 04 Jan 2011 00:39

Actions (login required)

View Item
View Item