A VLSI Spiking Feedback Neural Network with Negative Thresholding and Its Application to Associative Memory
Summary :
An integrate-and-fire-type spiking feedback network is discussed in this paper. In our spiking neuron model, analog information expressing processing results is given by the relative relation of spike firing. Therefore, for spiking feedback networks, all neurons should fire (pseudo-)periodically. However, an integrate-and-fire-type neuron generates no spike unless its internal potential exceeds the threshold. To solve this problem, we propose negative thresholding operation. In this paper, this operation is achieved by a global excitatory unit. This unit operates immediately after receiving the first spike input. We have designed a CMOS spiking feedback network VLSI circuit with the global excitatory unit for Hopfield-type associative memory. The circuit simulation results show that the network achieves correct association operation.
- Publication
- IEICE TRANSACTIONS on Electronics Vol.E89-C No.11 pp.1637-1644
- Publication Date
- 2006/11/01
- Publicized
- Online ISSN
- 1745-1353
- DOI
- 10.1093/ietele/e89-c.11.1637
- Type of Manuscript
- Special Section PAPER (Special Section on Novel Device Architectures and System Integration Technologies)
- Category
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Kan'ya SASAKI, Takashi MORIE, Atsushi IWATA, "A VLSI Spiking Feedback Neural Network with Negative Thresholding and Its Application to Associative Memory" in IEICE TRANSACTIONS on Electronics,
vol. E89-C, no. 11, pp. 1637-1644, November 2006, doi: 10.1093/ietele/e89-c.11.1637.
Abstract: An integrate-and-fire-type spiking feedback network is discussed in this paper. In our spiking neuron model, analog information expressing processing results is given by the relative relation of spike firing. Therefore, for spiking feedback networks, all neurons should fire (pseudo-)periodically. However, an integrate-and-fire-type neuron generates no spike unless its internal potential exceeds the threshold. To solve this problem, we propose negative thresholding operation. In this paper, this operation is achieved by a global excitatory unit. This unit operates immediately after receiving the first spike input. We have designed a CMOS spiking feedback network VLSI circuit with the global excitatory unit for Hopfield-type associative memory. The circuit simulation results show that the network achieves correct association operation.
URL: https://global.ieice.org/en_transactions/electronics/10.1093/ietele/e89-c.11.1637/_p
Copy
@ARTICLE{e89-c_11_1637,
author={Kan'ya SASAKI, Takashi MORIE, Atsushi IWATA, },
journal={IEICE TRANSACTIONS on Electronics},
title={A VLSI Spiking Feedback Neural Network with Negative Thresholding and Its Application to Associative Memory},
year={2006},
volume={E89-C},
number={11},
pages={1637-1644},
abstract={An integrate-and-fire-type spiking feedback network is discussed in this paper. In our spiking neuron model, analog information expressing processing results is given by the relative relation of spike firing. Therefore, for spiking feedback networks, all neurons should fire (pseudo-)periodically. However, an integrate-and-fire-type neuron generates no spike unless its internal potential exceeds the threshold. To solve this problem, we propose negative thresholding operation. In this paper, this operation is achieved by a global excitatory unit. This unit operates immediately after receiving the first spike input. We have designed a CMOS spiking feedback network VLSI circuit with the global excitatory unit for Hopfield-type associative memory. The circuit simulation results show that the network achieves correct association operation.},
keywords={},
doi={10.1093/ietele/e89-c.11.1637},
ISSN={1745-1353},
month={November},}
Copy
TY - JOUR
TI - A VLSI Spiking Feedback Neural Network with Negative Thresholding and Its Application to Associative Memory
T2 - IEICE TRANSACTIONS on Electronics
SP - 1637
EP - 1644
AU - Kan'ya SASAKI
AU - Takashi MORIE
AU - Atsushi IWATA
PY - 2006
DO - 10.1093/ietele/e89-c.11.1637
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E89-C
IS - 11
JA - IEICE TRANSACTIONS on Electronics
Y1 - November 2006
AB - An integrate-and-fire-type spiking feedback network is discussed in this paper. In our spiking neuron model, analog information expressing processing results is given by the relative relation of spike firing. Therefore, for spiking feedback networks, all neurons should fire (pseudo-)periodically. However, an integrate-and-fire-type neuron generates no spike unless its internal potential exceeds the threshold. To solve this problem, we propose negative thresholding operation. In this paper, this operation is achieved by a global excitatory unit. This unit operates immediately after receiving the first spike input. We have designed a CMOS spiking feedback network VLSI circuit with the global excitatory unit for Hopfield-type associative memory. The circuit simulation results show that the network achieves correct association operation.
ER -
English
