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 :
بازگشت