DocumentCode :
349137
Title :
High performance interconnection architecture for large cellular neural networks
Author :
Salerno, Mario ; Sargeni, Fausto ; Bonaiuto, Vincenzo
Author_Institution :
Dept. of Electron. Eng., Rome Univ., Italy
Volume :
1
fYear :
1998
fDate :
1998
Firstpage :
195
Abstract :
Several CNN hardware implementations have been presented in the last year. Most of them consist of one-chip circuits. Among the others, the authors presented the DPCNN chip family: a current-mode interconnection-oriented CNN analogue chip family. This approach presents many advantages and some drawbacks. In fact, simply connecting together more of these chips, it allows one to implement any size CNN arrays with the possibility to modify the network topology. On the other hand, it requires a high number of pads for the interconnections. Moreover, some parasitic capacitors due to the pads and the PCB wiring will appear. In this paper a high performance technique to improve the interconnection strategy able to overcome these drawbacks without any lack of functionality is presented
Keywords :
analogue processing circuits; cellular neural nets; integrated circuit interconnections; network topology; neural chips; CNN analogue chip; cellular neural networks; functionality; hardware implementations; interconnection architecture; network topology; parasitic capacitors; Capacitors; Cellular neural networks; Integrated circuit interconnections; Joining processes; Manufacturing; Network topology; Neural network hardware; Very large scale integration; Voltage control; Wiring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Circuits and Systems, 1998 IEEE International Conference on
Conference_Location :
Lisboa
Print_ISBN :
0-7803-5008-1
Type :
conf
DOI :
10.1109/ICECS.1998.813301
Filename :
813301
Link To Document :
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