Wiehler, KlausKlausWiehlerLembcke, RalphRalphLembckeGrigat, Rolf-RainerRolf-RainerGrigatHeers, JosefJosefHeersSchnörr, ChristophChristophSchnörrStiehl, Hans SiegfriedHans SiegfriedStiehl2021-08-312021-08-3119981998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications proceedings: 313-318 (1998)http://hdl.handle.net/11420/10214In [10] 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 1-d 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 this paper.enInformatikConference Paper10.1109/CNNA.1998.685393Other