DocumentCode :
1717867
Title :
Experimental verification of CNN (Cellular Neural Network)-based nonautonomous MLC chaos generator
Author :
Kiliç, Recai ; Günay, Enis ; Dalkiran, Fatma Y. ; Mutlu, Ümüt
Author_Institution :
Dept. of Electr. & Electron. Eng., Erciyes Univ., Kayseri, Turkey
fYear :
2011
Firstpage :
624
Lastpage :
627
Abstract :
In this paper, experimental verification of CNN-based nonautonomous MLC system designed as chaos generator is presented by using programmable and reconfigurable IC technique. The hardware implementation uses FPAA (Field Programmable Analog Array)-based reconfigurable design methodology. FPAA is a programmable IC and a rich variety of systems including analog functions can be realized via dynamic reconfiguration. Experimental results verify the CNN-based MLC chaos generator´s design methodology and that analog hardware solutions using FPAA device can be very effective for real implementation of CNN_based systems.
Keywords :
cellular neural nets; chaos generators; field programmable analogue arrays; FPAA; cellular neural network; field programmable analog array; nonautonomous MLC chaos generator; programmable IC technique; reconfigurable IC technique; reconfigurable design methodology; Bifurcation; Chaos; Educational institutions; Field programmable analog arrays; Generators; Hardware; Integrated circuit modeling; Cellular Neural Networks; FPAA (Field Programmable Analog Array); MLC Chaos Generator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuit Theory and Design (ECCTD), 2011 20th European Conference on
Conference_Location :
Linkoping
Print_ISBN :
978-1-4577-0617-2
Electronic_ISBN :
978-1-4577-0616-5
Type :
conf
DOI :
10.1109/ECCTD.2011.6043620
Filename :
6043620
Link To Document :
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