DocumentCode
3166158
Title
Test cases: emergent generalizations in the Athena and the Rumelhart´s neural net models
Author
Srikanth, Radhakrishnan ; Koutsougeras, Cris ; Bringman, M.W. ; Dandashi, Fatma
Author_Institution
Dept. of Comput. Sci., Tulane Univ., New Orleans, LA, USA
fYear
1990
fDate
1-4 Apr 1990
Firstpage
500
Abstract
The performances of Rumelhart´s nonlinear feedforward (NLFF) model and Athena are compared with respect to their generalization capabilities. The evaluation is based on a number of actual test cases. Evaluations are provided for the specific characteristics of the problems and the models involved, explaining the variations of their performances. The test cases presented illustrate the general type of problems which are particular to each model. The models have been applied on a few different types of learning tasks
Keywords
learning systems; neural nets; Athena; Rumelhart´s neural net models; learning tasks; nonlinear feedforward model; performance comparison; Computer aided software engineering; Computer science; Feedforward systems; Information retrieval; Neural networks; Performance evaluation; Testing; Wave functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Southeastcon '90. Proceedings., IEEE
Conference_Location
New Orleans, LA
Type
conf
DOI
10.1109/SECON.1990.117864
Filename
117864
Link To Document