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A sampled-data approach to optimal relaxed-causal sampling

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Abstract

This paper studies the design of an optimal relaxed causal sampler using sampled data system theory. A lifted frequency domain approach is used to obtain the existence conditions and optimal sampler. A state-space formulation of the results is also provided. The resulting optimal relaxed causal sampler is a cascade of a linear continuous-time system followed by a generalized sampler and a discrete system.

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Notes

  1. This condition is with the constraint that \(\breve{G}_{{\text{ v }}}\) is causal.

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Acknowledgements

We are thankful to Prof. Leonid Mirkin and Dr. Maxim Kristalny (Technion, Israel) for many helpful discussions and suggestions.

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Author notes

  1. Hanumant Singh Shekhawat

    Present address: Indian Institute of Technology Guwahati, Guwahati, India

Authors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Hanumant Singh Shekhawat & Gjerrit Meinsma

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  1. Hanumant Singh Shekhawat
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  2. Gjerrit Meinsma
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Correspondence to Hanumant Singh Shekhawat.

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The material in this paper was partially presented at the 20th International Symposium on Mathematical Theory of Networks and Systems (MTNS), July 9–13, 2012, Melbourne, Australia, with the title optimal relaxed causal sampler using sampled-data system theory.

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Shekhawat, H.S., Meinsma, G. A sampled-data approach to optimal relaxed-causal sampling. Math. Control Signals Syst. 33, 669–705 (2021). https://doi.org/10.1007/s00498-021-00297-9

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