A Spatial Domiain Sigma-Delta Modulator Using Discrete-Time Cellular Neural Networks

In this paper, a novel spatial domain sigma-delta modulator using discrete-time cellular neural networks (DT-CNNs) is proposed. Since the nature of CNN dynamics with the output function which has two saturation regions is to binarize the input image, CNNs have a capabilities as a spatial domain sigma-delta modulator. In the proposed architecture, the A-template is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output. Moreover, the dynamics is designed for obtaining an optimal reconstruction image. The experimental results show a good reconstruction performance and capabilities of CNN as a sigma-delta modulator