DocumentCode :
302557
Title :
About the robustness of CNN linear templates with bipolar images
Author :
Paasio, Ari ; Dawidziuk, Adam ; Halonen, Kari ; Porra, Veikko
Author_Institution :
Electron. Circuit Design Lab., Helsinki Univ. of Technol., Espoo, Finland
Volume :
3
fYear :
1996
fDate :
12-15 May 1996
Firstpage :
555
Abstract :
This paper defines robustness measures for CNN linear templates. The measures are described for the normal unity gain CNN and also for a very high gain CNN. Inaccuracies in templates are next introduced and formulas for new modified measures are defined. This information can be very useful to CNN hardware designers when determining the acceptable inaccuracies in the coefficient realizations. If some template is found not to be good in presence of inaccuracies the robustness can be increased. One way to increase the defined template robustness is discussed. The increase in robustness factors are calculated and finally one example is given for the use of the described method
Keywords :
VLSI; cellular neural nets; neural chips; stability; CNN linear templates; bipolar images; cellular neural networks; coefficient realizations; high gain CNN; normal unity gain CNN; robustness measures; template robustness improvement; Cellular neural networks; Electronic circuits; Gain measurement; Hardware; Robustness; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3073-0
Type :
conf
DOI :
10.1109/ISCAS.1996.541656
Filename :
541656
Link To Document :
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