CNN Technology for Spatiotemporal Signal Processing

Call for Papers

A cellular neural/nonlinear network (CNN) is any spatial arrangement of mainly locallycoupled cells, where each cell has an input, an output, and a state that evolves according to some prescribed dynamical laws. CNN represents a paradigm for nonlinear spatial-temporal dynamics and the core of the cellular wave computing (also called CNN technology). Partial differential equations (PDEs) or wave-like phenomena are the computing primitives of CNN. Besides, their suitability for physical implementation due to their local connectivity makes CNNs very appropriate for high-speed parallel signal processing.

Early CNN applications were mainly in image processing. The possible availability of cellular processor arrays with a high number of processing elements opened a new window 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 contours or active wave propagation, or applications within the medical image processing framework (echocardiography, retinal image processing, etc.) where fast processing provides new capabilities for medical disease diagnosis.

On the other hand, emerging applications exploit the complex spatiotemporal phenomena exhibited by multilayer CNN and extend to the modelling of neural circuits for biological vision, motion, and higher brain function.

The aim of this special issue is to bring forth the synergy between CNN and spatiotemporal signal processing through new and significant contributions from active researchers in these fields. Topics of interest include, but are not limited to:

  • Theory of cellular nonlinear spatiotemporal phenomena
  • Analog-logic spatiotemporal algorithms
  • Learning & design
  • Bioinspired/neuromorphic arrays
  • Physical VLSI implementations: integrated sensor/processor/actuator arrays
  • Applications including computing, communications, and multimedia
  • Circuits, architectures and systems in the nanoscale regime
  • Other areas in cellular neural networks and array computing

Authors should follow the EURASIP Journal on Advances in Signal Processing manuscript format described at http://www.hindawi.com/journals/asp/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/, according to the following timetable:

Manuscript DueSeptember 15, 2008
First Round of ReviewsDecember 15, 2008
Publication DateMarch 15, 2009

Guest Editors:

  • David López Vilariño, Departamento de Electrónica y Computación, Facultad de Fisica, Universidad de Santiago de Compostela, 15782 Santiago de Compostela, Spain
  • Diego Cabello Ferrer, Departamento de Electrónica y Computación, Facultad de Fisica, Universidad de Santiago de Compostela, 15782 Santiago de Compostela, Spain
  • Victor M. Brea, Departamento de Electrónica y Computación, Facultad de Fisica, Universidad de Santiago de Compostela, 15782 Santiago de Compostela, Spain
  • Ronald Tetzlaff, Lehrstuhl für Grundlagen der Elektrotechnik, Fakultät für Elektrotechnik und Informationstechnik, Technische Universität Dresden, Mommsenstraße 12, 01069 Dresden, Germany
  • Chin-Teng Lin, National Chiao-Tung University, Hsinchu 300, Taiwan