Paper
1 September 1993 Reconfigurating feedforward networks with fewer hidden nodes
Iwao Sekita, Takio Kurita, David K. Y. Chiu, H. Asoh
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Abstract
The number of nodes in a hidden layer of a feedforward layered network reflects an optimality condition of the network in coding a function. It also affects the computation time and the ability of the network to generalize. When an arbitrary number of hidden nodes is used in designing the network, redundancy of hidden nodes often can be seen. In this paper, a method of reducing hidden nodes is proposed on the condition that a reduced network maintains the performances of the original network with accepted level of tolerance. This method can be applied for estimation of performances of a network with fewer hidden nodes. The estimated performances are the lower bound of the actual performances of the network. Experiments were performed on the Fisher's IRIS data, a set of SONAR data, and the XOR data for classification. Their results suggest that sufficient number of hidden nodes, fewer than the original number, can be estimated by the present method.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Iwao Sekita, Takio Kurita, David K. Y. Chiu, and H. Asoh "Reconfigurating feedforward networks with fewer hidden nodes", Proc. SPIE 1962, Adaptive and Learning Systems II, (1 September 1993); https://doi.org/10.1117/12.150596
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
IRIS Consortium

Principal component analysis

Tolerancing

Data analysis

Information science

Network architectures

Neural networks

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