DocumentCode
3241155
Title
Handling knowledge in high order neural networks: the combinatorial neural model
Author
Machado, Ricardo J.
Author_Institution
IBM, Rio de Janeiro, Brazil
fYear
1989
fDate
0-0 1989
Abstract
Summary form only given, as follows. A description is given of the combinatorial neural model, a high-order neural network suitable for classification tasks. The model is based on fuzzy set theory, neural sciences studies, and expert knowledge analysis results. It presents interesting properties such as modularity, explanation capacity, knowledge and data representation, high speed of training, incremental learning, generalization capacity, processing of uncertain and incomplete data, and ability to reason nonmonotonically when representing only relevant evidence, and graceful decay.<>
Keywords
explanation; fuzzy set theory; knowledge representation; neural nets; classification; combinatorial neural model; data representation; expert knowledge analysis; explanation capacity; fuzzy set theory; generalization capacity; high order neural networks; incomplete data; incremental learning; knowledge representation; modularity; neural nets; neural sciences; nonmonotonic reasoning; training; uncertain data; Explanation; Fuzzy sets; Knowledge representation; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1989. IJCNN., International Joint Conference on
Conference_Location
Washington, DC, USA
Type
conf
DOI
10.1109/IJCNN.1989.118339
Filename
118339
Link To Document