Title :
CNN chip and FPGA to explore complexity
Author :
Arena, P. ; Fortuna, L. ; Vagliasindi, G. ; Basile, A.
Author_Institution :
Dipt. di Ingegneria Elettrica, Elettronica e dei Sistemi, Universita degli Studi di Catania, Italy
Abstract :
The novel ACE16Kv1 chip has proved the performances of the cellular nonlinear networks. Its signal processing capabilities need a powerful interface to be exploited. In this paper, the authors would present the main outline of a project able to carry out the fully performance of the ACE16Kv1 chip and its core in order to study the emergent chaotic dynamics. The hardware system has been mainly based on two chips: the ACE16Kv1 and a FPGA, which interface the 128×128 CNN cells with a PC, where a high-level program permits to interact with the system.
Keywords :
cellular neural nets; circuit complexity; field programmable gate arrays; ACE16Kv1 chip; CNN chip; FPGA; cellular nonlinear networks; circuit complexity; signal processing; CMOS image sensors; Cellular networks; Cellular neural networks; Chaos; Differential equations; Field programmable gate arrays; Focusing; Hardware; Nonlinear dynamical systems; Very large scale integration;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
Print_ISBN :
0-7803-9185-3
DOI :
10.1109/CNNA.2005.1543184
