AUXIL\
ffnkal__define.pro
Class description for FFNKAL
Inheritance
Fields
Fields in FFN
- N ptr_new()
- KK 0L
- NN 0L
- NP 0L
- WH ptr_new()
- LL 0L
- WO ptr_new()
- LS ptr_new()
- GS ptr_new()
Fields in FFNKAL
- SH ptr_new()
- SO ptr_new()
- VALID_COST_ARRAY ptr_new()
- ITERATIONS 0L
- COST_ARRAY ptr_new()
Routines
result = FFNKAL::Init(Gs, Ls, L)Object class for implementation of a two-layer, feed-forward neural network classifier.
FFNKAL::CleanupFFNKAL::train, key=keyFFNKAL__Define
Routine details
top FFNKAL::Init
result = FFNKAL::Init(Gs, Ls, L)
Object class for implementation of a two-layer, feed-forward neural network classifier. Implements Kalman filter training:
Shah, S. and Palmieri, F. (1990). Meka — A fast,
local algorithm for training feed forward neural
networks. Proceedings of the International Joint
Conference on Neural Networks, San Diego, I(3),
41–46.
Parameters
- Gs in required
array of observation column vectors
- Ls in required
array of class label column vectors of form (0,0,1,0,0,...0)^T
- L in required
number of hidden neurons
Examples
ffn = Obj_New("FFNKAL",Gs,Ls,L)
Author information
- Author:
Mort Canty (2009)
Other attributes
- Uses:
COYOTE
top FFNKAL::Cleanup
FFNKAL::Cleanup
top FFNKAL__Define
FFNKAL__Define
File attributes
| Modification date: | Mon Mar 03 16:33:25 2014 |
| Lines: | 165 |
| Docformat: | rst rst |