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Architecture of a Fully Pipelined Real-Time Cellular Neural Network Emulator.

Authors :
Yildiz, Nerhun
Cesur, Evren
Kayaer, Kamer
Tavsanoglu, Vedat
Alpay, Murathan
Source :
IEEE Transactions on Circuits & Systems. Part I: Regular Papers. Jan2015, Vol. 62 Issue 1, p130-138. 9p.
Publication Year :
2015

Abstract

In this paper, architecture of a Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v2) is given and the implementation results are discussed. The proposed architecture has a fully pipelined structure, capable of processing full-HD 1080p@60 (1920 \times 1080 resolution at 60 Hz frame rate, 124.4 MHz visible pixel rate) video streams, which is implemented on both high-end and low-cost FPGA devices, Altera Stratix IV GX 230, and Cyclone III C 25, respectively. Many features of the architecture are designed to be either pre-synthesis configurable or runtime programmable, which makes the processor extremely flexible, reusable, scalable, and practical. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15498328
Volume :
62
Issue :
1
Database :
Academic Search Index
Journal :
IEEE Transactions on Circuits & Systems. Part I: Regular Papers
Publication Type :
Periodical
Accession number :
100348592
Full Text :
https://doi.org/10.1109/TCSI.2014.2345502