DocumentCode :
3633556
Title :
A low power current-mode binary-tree WTA / LTA circuit for Kohonen neural networks
Author :
Rafal Dlugosz;Tomasz Talaska
Author_Institution :
Institute of Microtechnology, Swiss Federal Institute of Technology in Lausanne (EPFL), Neuchatel, Switzerland
fYear :
2009
Firstpage :
201
Lastpage :
204
Abstract :
A novel current-mode, binary-tree WTA / LTA circuit for application in analog Kohonen neural networks has been presented. In the proposed circuit input currents are first converted to step signals with equal amplitudes and different delays that are proportional to the values of these currents. In the second step these delays are compared using a set of time domain comparators in the binary tree structure that allows to determine either the Min or the Max signal, depending on the configuration. The circuit realized in the TSMC CMOS 0.18 µm process offers a precision of about 99 % at the data rate of 3.5 MSps and energy consumption of about 0.7 pJ per one input signal per cycle.
Keywords :
"Neural networks","Signal processing","Binary trees","Coupling circuits","MOSFETs","Artificial neural networks","Image processing","Filters","Delay","Energy consumption"
Publisher :
ieee
Conference_Titel :
Mixed Design of Integrated Circuits & Systems, 2009. MIXDES ´09. MIXDES-16th International Conference
Print_ISBN :
978-1-4244-4798-5
Type :
conf
Filename :
5289636
Link To Document :
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