Cort-X II: The Low-Power Element Design for a Dynamic Neural Network

Autor:	Jie Yuan, Ning Song, J. Van der Spiegel, Nabil H. Farhat
Rok vydání:	2007
Předmět:	Interconnection Engineering Recurrent neural network Artificial neural network business.industry Low-power electronics Electronic engineering Energy consumption Electrical and Electronic Engineering Logistic map Cluster analysis business Power (physics)
Zdroj:	IEEE Transactions on Circuits and Systems II: Express Briefs. 54:1130-1134
ISSN:	1558-3791 1549-7747
DOI:	10.1109/tcsii.2007.905882
Popis:	The parametrically coupled logistic map network (PCLMN) can serve as the front-end dynamic neural network (DNNs) for clustering and generation of spatio-temporal patterns. In this brief, the element of the PCLMN is designed in a 0.25-mum 2.5-V CMOS process for low power consumption. The analog design employs self-calibration techniques to improve the accuracy of the low-power element. After calibration, the fabricated element is able to generate a 1-D map and the nonlinear interconnection in 4-bit resolution for driving signals up to 1 MHz, with a power consumption of 12 mW.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::defcd51f72353484526df4e945824cfb https://doi.org/10.1109/tcsii.2007.905882 Zobrazit plný text záznamu