In this paper, a multi-chip expandable modified feedforward Hamming neural network for pattern classification is designed and implemented. In the proposed modified Hamming network, the outstar circuit is used to provide the on-chip learning capability. Moreover, the embedded ratio memory in the outstar circuit is used to store the learned pattern. The chips can be connected to form pattern, element, and pattern-and-element-mixed expansions. The experimental results have been correctly verified the operation of multi-chip expansion and classification function. The contrast enhancement characteristic of the stored pattern in the 3-chip element expansion has also been observed.
|Number of pages||4|
|Journal||Proceedings - IEEE International Symposium on Circuits and Systems|
|State||Published - 1 Jan 1997|
|Event||Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4) - Hong Kong, Hong Kong|
Duration: 9 Jun 1997 → 12 Jun 1997