Dynamic circular cellular networks for adaptive smoothing of multi-dimensional signals

In Schnorr et al. (1996) a theoretical framework for locally-adaptive smoothing of multi-dimensional data was presented. Based on this framework we introduce a hardware efficient architecture suitable for mixed-mode VLSI implementation. Substantial shortcomings of analogue implementations are overcome by connecting all cells in a circular structure: (i) influence of process parameter deviation, (ii) limited number of cells, (iii) input/output bottleneck. The connections between the analogue cells and the cells themselves are dynamically reconfigured. This results in a non-linear adaptive filter kernel which is shifted virtually over the signal vector of infinite length. A 1D prototype with 32 cells has been fabricated using 0.8 μm CMOS-technology. The chip is fully functional with an overall error less than 1%; experimental results are presented in the paper