Title :
Silicon experimentation of first order TDCNN dynjamics
Author :
Ip, H.M.D. ; Drakakis, E.M. ; Bharath, A.A.
Author_Institution :
Dept. of Bioeng., Imperial Coll. London, London, UK
Abstract :
Recently, the authors have proposed a network formalism (TDCNNs) which introduces Time-Derivative coupling between linearized-CNN cells (with output nonlinearity removed) and demonstrated its use in realizing non-separable 3D spatiotemporal filters. TDCNNs assume inputs in the form of time-varying 2D array of pixels and processing is carried out in continuous-time. Due to this continuous-time nature of TDCNNs, it can be conveniently implemented with an array of continuous-time filters, each coupled to its nearest neighbors according to the feedforward/feedback and temporal-derivative templates. Analog circuit building blocks and simulation results from our first attempt in implementing TDCNNs with full custom CMOS was presented previously. This paper follows from our previous presentation and includes some of the measured results obtained from the fabricated prototype with 5 ?? 5 two-layered cells.
Keywords :
VLSI; cellular neural nets; continuous time filters; time-varying filters; 3D spatiotemporal filters; analog circuit building blocks; continuous-time filters; continuous-time nature; first order TDCNN Dynjamies; linearized CNN cells; network formalism; silicon experimentation; temporal-derivative templates; time-derivative coupling; time-varying 2D array; Analog circuits; CMOS analog integrated circuits; Circuit simulation; Coupling circuits; Feedback; Filters; Nearest neighbor searches; Prototypes; Silicon; Spatiotemporal phenomena; Analog VLSI; Cellular Neural Networks; Continous time filtering;
Conference_Titel :
Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on
Conference_Location :
Berkeley, CA
Print_ISBN :
978-1-4244-6679-5
DOI :
10.1109/CNNA.2010.5430273