Abstract
In this chapter some implementation constraints are introduced in the adaptation procedure. As a result, no closed-form design rule can be given and more sophisticated optimization tools are developed. The overall algorithmic complexity of the acquisition procedure is also considered and a knob controlling it is introduced. This further degree of freedom is shown to allow the administration of the trade-off between acquisition complexity and the quality of the reconstructed signal.
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D. Bellasi et al., A low-power architecture for punctured compressed sensing and estimation in wireless sensor-nodes. IEEE Trans. Circuits Syst. I Regul. Pap. 62(5), 1296–1305 (2015)
J.P. Boyle, R.L. Dykstra, A method for finding projections onto the intersection of convex sets in Hilbert spaces, in Advances in Order Restricted Statistical Inference, ed. by R.L. Dykstra, T. Robertson, F.T. Wright. Proceedings of the Symposium on Order Restricted Statistical Inference Held in Iowa City Iowa, September 11–13, 1985 (Springer New York, New York, 1986), pp. 28–47
A.A. Goldstein, Convex programming in Hilbert space. Bull. Am. Math. Soc. 70, 709–710 (1964)
J. Haboba et al., A pragmatic look at some compressive sensing architectures with saturation and quantization. IEEE J. Emerging Sel. Top. Circuits Syst. 2(3), 443–459 (2012)
J. Von Neumann, On rings of operators. Reduction theory. Ann. Math. 50(2), 401–485 (1949)
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Mangia, M., Pareschi, F., Cambareri, V., Rovatti, R., Setti, G. (2018). The Rakeness Problem with Implementation and Complexity Constraints. In: Adapted Compressed Sensing for Effective Hardware Implementations. Springer, Cham. https://doi.org/10.1007/978-3-319-61373-4_4
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DOI: https://doi.org/10.1007/978-3-319-61373-4_4
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-61372-7
Online ISBN: 978-3-319-61373-4
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