DocumentCode
2516640
Title
Random variations in CNN templates: theoretical models and empirical studies
Author
Shi, B.E. ; Wendsche, S. ; Roska, T. ; Chua, L.O.
Author_Institution
Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, Hong Kong
fYear
1994
fDate
18-21 Dec 1994
Firstpage
27
Lastpage
32
Abstract
This paper studies the performance of binary image processing CNN templates when the actual template values at each cell are allowed to vary from their nominal values. We examine the validity of one plausible measure of the robustness to random template variations: the minimum absolute value of the current into the capacitor taken over all possible binary state patterns divided by the norm of the template elements. While this measure can be proven to be a valid indicator of robustness for linear threshold templates, its predictive power on the more dynamically complex CCD template is mixed. In some cases, an estimate of the error rate based upon this measure matches remarkably well with the results of numerical simulations. In others, this measure of robustness predicts that one template is more robust than another, while numerical simulations indicate that the opposite is true
Keywords
cellular neural nets; image processing; CNN templates; binary image processing; empirical studies; error rate; random template variations; robustness; theoretical models; Cellular neural networks; Charge coupled devices; Cloning; Image processing; Indexing; Numerical simulation; Piecewise linear techniques; Power measurement; Robustness; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
Conference_Location
Rome
Print_ISBN
0-7803-2070-0
Type
conf
DOI
10.1109/CNNA.1994.381684
Filename
381684
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