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Abstract
A new approach to Cellular Neural Networks discrete model is proposed. This approach is focused on CNN implementation on reconfigurable hardware architectures and DSP microprocessors. CNN are analysed from the perspective of Systems Theory, giving rise to an alternative model to those found in the literature available. Dynamic equations and their solutions, stability analysis and real-time implementation architecture are described in this paper as the most relevant points in the development of our model. The main results, obtained from different simulations, evidence the usefulness and functionality of the model.
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Authors and Affiliations
Dpto. Electrónica, Tecnología de Computadoras y Proyectos, Universidad Politécnica de Cartagena, Campus Muralla del Mar, C/ Dr. Fleming s/n, 30202, Cartagena, Spain
J.J. Martínez, F.J. Toledo & J.M. Ferrández
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E.T.S. de Ingeniería Informática Departamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Juan del Rosal, 16, 28040, Madrid, Spain
José Mira & José R. Álvarez &
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Martínez, J., Toledo, F., Ferrández, J. (2003). New emulated discrete model of CNN architecture for FPGA and DSP applications. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_5
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