Title :
Current Mode Euclidean Distance Calculation Circuit for Kohonen´s Neural Network Implemented in CMOS 0.18?m Technology
Author :
Tomasz Talaska;Rafal Dlugosz
Author_Institution :
Univ. of Technol. & Life Sci., Bydgoszcz
fDate :
4/1/2007 12:00:00 AM
Abstract :
In this paper we present analog current mode Euclidean distance calculation (EDC) block, which calculates the distance between two current vectors. The proposed circuit is an important part of the CMOS-implemented Kohonen´s neural network (KNN) designed for medical applications. The input data vector is compared with the weights´ vector in each neuron in proposed KNN. The neuron, whose weights are the closest to the input training vector becomes the winner and in the next step changes its weights. Proposed EDC block performs several operations such as: subtraction, squaring and summing of the current signals. The output current is the exact measure of the Euclidean distance. Proposed circuit dissipates power 15 muW from 1.5 V voltage supply, working with 20 MHz input data frequency. The signal frequency as well as the power dissipation may be scaled down to 1 MHz and 300 nA. Proposed EDC circuit, in CMOS 0.18 mum technology, occupies area about 500 mum2.
Keywords :
"CMOS technology","Euclidean distance","Circuits","Neural networks","Neurons","Frequency","Medical services","Biomedical equipment","Current measurement","Voltage"
Conference_Titel :
Electrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
Print_ISBN :
1-4244-1020-7
DOI :
10.1109/CCECE.2007.115