Title :
A Note on the Fast BRAIN Learning Algorithm
Author :
Xu, Shuo ; Tao, Lan ; An, Xin ; Li, Lin
Author_Institution :
Coll. of Inf. & Electr. Eng., China Agric. Univ., Beijing
Abstract :
In this paper, an underlying problem on the fast BRAIN learning algorithm is pointed out, which is avoided by introducing the quantity count (middot, middot). In addition, its speed advantage can still be enjoyed only at a cost of a little additional space. The improved fast BRAIN learning algorithm is also given, and the experiments on NN269 dataset validate our analysis.
Keywords :
biology computing; learning (artificial intelligence); NN269 dataset; fast BRAIN learning algorithm; quantity count; Agricultural engineering; Algorithm design and analysis; Biomedical engineering; Biomedical informatics; Costs; Data analysis; Educational institutions; International trade; Learning; Neural networks; BRAIN; Numerical Computation; Splice Sites Prediction;
Conference_Titel :
BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-0-7695-3118-2
DOI :
10.1109/BMEI.2008.79
