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Publication detail
DAO ANH, M. ZBOŘIL, F.
Original Title
Tuning of Fuzzy Neural Network Classifier
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
The paper delas with a Fuzzy Restricted Coulomb Energy (FRCE) neural network. The network has the same architecture as a primitive RCE neural network: it consists of three layers: input layer X, hidden layer H (prototype layer) and output layer Y. There is a full set of connections between input and prototype layers, but only partial set of connections exits between hidden and output layers. Each neuron in the input layer represents a feature of an incoming pattern that the network must assign to some pattern class. Each neuron in the hidden layer contains information about an example of a learned class that occurs in the training data. In the output layer, each neuron corresponds to an individual class, i.e. it represents one category of patterns. The FRCE principle and it structure, learning an recalling algorithms and some experiments with FRCE are described in the paper.
Keywords
Fuzzy Sets, Neural Network, Fuzzy Pattern Recognition, Restricted Coulomb Energy, Fuzzy Neural Network.
Authors
DAO ANH, M.; ZBOŘIL, F.
RIV year
2001
Released
9. 5. 2001
Location
Ostrava
ISBN
80-85988-57-7
Book
Proceedings of the 35th Spring International Conference MOSIS'01
Pages from
201
Pages to
206
Pages count
6
BibTex
@inproceedings{BUT5591, author="Minh {Dao Anh} and František {Zbořil}", title="Tuning of Fuzzy Neural Network Classifier", booktitle="Proceedings of the 35th Spring International Conference MOSIS'01", year="2001", pages="201--206", address="Ostrava", isbn="80-85988-57-7" }