Title :
Pattern matching and classification based on an associative memory architecture using CRS
Author :
Cho, Kyoungrok ; Lee, Sang-Jin ; Oh, Kwang-Seok ; Han, Ca-Ram ; Kavehei, Omid ; Eshraghian, Kamran
Author_Institution :
Dept. of Electr. & Electron. Eng., Chungbuk Nat. Univ., Cheongju, South Korea
Abstract :
Emergence of new materials and in particular the recent progress in Memristor and related memory technologies encouraged the research community for a renewed approach towards formulation of architectures such as those that depend upon associate memory constructs to take the advantages being offered within this new design domain. In this paper we address a key issue in pattern matching and classification process and hence suggest an alternative approach for image vector matching combining Complementary Resistive Switch (CRS) array and bump circuits. We emulated an experimental pattern matching with two approaches which are based on Hamming distance and threshold level of the image: the former finds an exact image with a bump circuit and the later finds similar patterns from the stored images combining comparators. The proposed hardware oriented architecture is high speed and smaller size that is easier to implement on conventional CMOS technology.
Keywords :
CMOS memory circuits; comparators (circuits); content-addressable storage; image classification; image matching; image segmentation; logic arrays; memory architecture; memristors; vectors; CMOS technology; CRS array; Hamming distance; associative memory architecture; bump circuits; comparators; complementary resistive switch array; design domain; hardware oriented architecture; image vector matching; memristor; pattern classification; pattern matching; threshold level; Arrays; Associative memory; Hamming distance; Pattern matching; Switches; Vectors;
Conference_Titel :
Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on
Conference_Location :
Turin
Print_ISBN :
978-1-4673-0287-6
DOI :
10.1109/CNNA.2012.6331433