Abstract
This paper presents a case study for the overlapped multi-neural-network (OMNN). An overlapped multi-neural-network, structurally, is the same as an ordinary feedforward neural network, but it is considered as one consisting of several subnets. All subnets have the same input-output units, but some different hidden units. Input-output spaces are partitioned into several parts, each of which corresponds to one subnet of OMNN. Numerical simulations show that such an OMNN has superior performance in that it has better presentation ability than an ordinary neural network and better generalization ability than a non-overlapped multi-neural-network.
| Original language | English |
|---|---|
| Pages | 120-125 |
| Number of pages | 6 |
| Publication status | Published - 2000 Jan 1 |
| Externally published | Yes |
| Event | International Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy Duration: 2000 Jul 24 → 2000 Jul 27 |
Other
| Other | International Joint Conference on Neural Networks (IJCNN'2000) |
|---|---|
| City | Como, Italy |
| Period | 00/7/24 → 00/7/27 |
ASJC Scopus subject areas
- Software
- Artificial Intelligence
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Cite this
Hu, J., & Hirasawa, K. (2000). Overlapped multi-neural-network: A case study. 120-125. Paper presented at International Joint Conference on Neural Networks (IJCNN'2000), Como, Italy, .