Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Editorial CNN Technology for Spatiotemporal Signal Processing | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 854806 2 pages doi 2009 854806 Editorial CNN Technology for Spatiotemporal Signal Processing David Lopez Vilarino 1 Diego Cabello Ferrer 1 Victor Manuel Brea Sanchez 1 Ronald Tetzlaff 2 and Chin-Teng Lin3 1 University of Santiago de Compostela Spain 2 Dresden University of Technology Germany 3National Chiao-Tung University NCTU Hsinchu Taiwan Correspondence should be addressed to David Lopez Vilarino Received 18 October 2009 Accepted 18 October 2009 Copyright 2009 David Lopez Vilarino et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Cellular Neural Networks CNNs are a paradigm for nonlinear spatial-temporal dynamics and the core of the Cellular Wave Computing also called CNN technology . Partial Differential Equations PDE or wave-like phenomena are the computing primitives of CNN. Besides their suitability for physical implementation makes CNNs very appropriate for high-speed parallel signal processing. Since its inception by Professor Chua in 1988 who defined a CNN as an arrangement of regularly spaced cells which usually communicate with each other through their nearest neighbors 1 many advances in theory applications and implementation have emerged. Early CNN applications were mainly focused on image processing. The availability of cellular processor arrays with a high number of processing elements paved the way for the development of new applications and the recovery of techniques traditionally conditioned by the slow speed of conventional computers. Let us name as example image processing techniques based on active wave propagation or applications within the medical image processing framework where fast processing provides new capabilities for medical disease .
