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Square-Root-Domain Realization of Single-Cell Architecture of Complex TDCNN

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Abstract

Square-root-domain (SRD) CMOS analog realization of a single cell architecture of the complex Temporal Derivative Cellular Neural Networks (TDCNNs) is introduced in this paper. TDCNN initiates time derivative ‘diffusion’ between CNN cells for non-separable spatiotemporal filtering applications, where the input to the CNN is an image that changes over time. The evaluation of the performance of the complex SRD TDCNN cell has been done using the Cadence Orcad software with TSMC 0.18-μm CMOS process model parameters. The provided simulated results confirm the validity of the theory.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their constructive comments and suggestions, which enhanced the clarity of this manuscript. This research has been financed by the University Grants Commission (UGC) New Delhi India under Major Research Project Financial Assistance Scheme No. 39-558/2010 (SR), dated 10 Jan. 2011. We would like to profoundly acknowledge UGC for their support.

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Authors and Affiliations

  1. Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar, 190 006, India

    Farooq A. Khanday & Nisar A. Shah

  2. Physics Department, Electronics Laboratory, University of Patras, 26504, Rio Patras, Greece

    Costas Psychalinos

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  1. Farooq A. Khanday
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  2. Costas Psychalinos
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  3. Nisar A. Shah
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Correspondence to Farooq A. Khanday.

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Khanday, F.A., Psychalinos, C. & Shah, N.A. Square-Root-Domain Realization of Single-Cell Architecture of Complex TDCNN. Circuits Syst Signal Process 32, 959–978 (2013). https://doi.org/10.1007/s00034-012-9503-1

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  • DOI: https://doi.org/10.1007/s00034-012-9503-1

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