Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
An Introduction to Fuzzy Logic Applications in Intelligent Systems
An Introduction to Fuzzy Logic Applications in Intelligent Systems
A geometrical representation of McCulloch-Pitts neural model and its applications
IEEE Transactions on Neural Networks
Programming based learning algorithms of neural networks with self-feedback connections
IEEE Transactions on Neural Networks
A modified constructive fuzzy neural networks for classification of large-scale and complicated data
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
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By introducing the principle and characteristics of constructive neural networks (CNN) and pointing out its deficiencies, fuzzy theory is adopted to improve the covering algorithms in this paper. We build “extended area” for each type of samples, eliminate the inference of the outlier, and redefine the threshold of covering algorithms. Furthermore, “sphere neighborhood” (SN) are constructed, the membership functions of test samples are given and all of the test samples are determined accordingly. First of all, the procedure of constructive fuzzy algorithm is given, then the model of constructive fuzzy neural networks (CFNN) is built, finally, CFNN is applied to search for communications signals. Extensive experimental results demonstrate the efficiency and practicability of the proposed algorithm.