Abstract
The effects of linear quantized Hebbian-type associative memories (HAMs) on storage capacity and hardware implementations are explored in this paper. For the linear quantization, the interconnection weights are linearly quantized into a small number of levels. This consideration focuses mainly on the situation when only a limited accuracy range can be achieved on hardware implementations. Results of simulation and theory show that the number of quantization levels required is relatively small compared with the possible values of interconnections. Therefore, linear quantization in HAMs is worthwhile in hardware implementations.
| Original language | English |
|---|---|
| Pages | 1092-1096 |
| Number of pages | 5 |
| Publication status | Published - 1994 Dec 1 |
| Event | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA Duration: 1994 Jun 27 → 1994 Jun 29 |
Other
| Other | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) |
|---|---|
| City | Orlando, FL, USA |
| Period | 94-06-27 → 94-06-29 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Software
Cite this
}
Linear quantization of Hebbian-type associative memories in interconnection implementations. / Chung, Pau Choo; Tsai, Ching Tsorng; Sun, Yung Nien.
1994. 1092-1096 Paper presented at Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7), Orlando, FL, USA, .Research output: Contribution to conference › Paper
TY - CONF
T1 - Linear quantization of Hebbian-type associative memories in interconnection implementations
AU - Chung, Pau Choo
AU - Tsai, Ching Tsorng
AU - Sun, Yung Nien
PY - 1994/12/1
Y1 - 1994/12/1
N2 - The effects of linear quantized Hebbian-type associative memories (HAMs) on storage capacity and hardware implementations are explored in this paper. For the linear quantization, the interconnection weights are linearly quantized into a small number of levels. This consideration focuses mainly on the situation when only a limited accuracy range can be achieved on hardware implementations. Results of simulation and theory show that the number of quantization levels required is relatively small compared with the possible values of interconnections. Therefore, linear quantization in HAMs is worthwhile in hardware implementations.
AB - The effects of linear quantized Hebbian-type associative memories (HAMs) on storage capacity and hardware implementations are explored in this paper. For the linear quantization, the interconnection weights are linearly quantized into a small number of levels. This consideration focuses mainly on the situation when only a limited accuracy range can be achieved on hardware implementations. Results of simulation and theory show that the number of quantization levels required is relatively small compared with the possible values of interconnections. Therefore, linear quantization in HAMs is worthwhile in hardware implementations.
UR - http://www.scopus.com/inward/record.url?scp=0028744833&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0028744833&partnerID=8YFLogxK
M3 - Paper
AN - SCOPUS:0028744833
SP - 1092
EP - 1096
ER -