Summary
International Symposium on Nonlinear Theory and its Applications
2008
Session Number:B4L-D
Session:
Number:B4L-D3
Functional Sigma-Delta CNN
Hisashi Aomori, Mamoru Tanaka,
pp.-
Publication Date:2008/9/7
Online ISSN:2188-5079
Summary:
A sigma-delta modulation is a well-known concept for analog-to-digital (A/D) converter. However, its underlying concept is limited to 1-D signals. The Sigma-Delta Cellular Neural Network (SD-CNN) is an efficient framework for a spatial domain sigma-delta modulation. Due to a CNN dynamics, each pixel of an image corresponds to a cell of a CNN, and each cell is connected spatially by the A-template. Therefore, the SD-CNN can be thought of as a very large-scale and super-parallel sigma-delta modulator. In this paper, we propose a novel functional sigma-delta modulation using SD-CNN. In order to provide new functions for SD-CNN, the essential conditions for constructing a spatial-domain sigma-delta modulation of CNN are reexamined. Multibit SD-CNN for high image reconstruction performance and SD-CNN with basic image processing ability for an integrated camera interface are proposed in this paper.