Deconvolution ISTA: A solver for multidimensional convolution problems with low computational complexity-Reference-Cited by-同舟云学术

Deconvolution ISTA: A solver for multidimensional convolution problems with low computational complexity

Published:2022-12-01 Issue:12 Volume:11 Page:784-790
ISSN:2187-0136
Container-title:IEICE Communications Express
language:en
Short-container-title:IEICE ComEX

Author:

Gocho Masanori¹

Affiliation:

1. National Institute of Information and Communications Technology

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

General Medicine

Link

https://www.jstage.jst.go.jp/article/comex/11/12/11_2022COL0023/_pdf

Reference10 articles.

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2. [2] I. Daubechies, M. Defrise, and C. De Mol, “An iterative thresholding algorithm for linear inverse problems with a sparsity constraint,” Communications on Pure and Applied Mathematics: A Journal Issued by the Courant Institute of Mathematical Sciences, vol. 57, no. 11, pp. 1413-1457, 2004. DOI: 10.1002/cpa.20042

3. [3] S. Foucart and H. Rauhut, “An invitation to compressive sensing,” in A Mathematical Introduction to Compressive Sensing, pp. 1-39, Springer, 2013. DOI: 10.1007/978-0-8176-4948-7_1

4. [4] M. Gocho and H. Yamada, “A proposal for sparse deconvolution using ISTA with low computational complexity,” Proc. of 2020 International Conference on Emerging Technologies for Communications (ICETC2020), G1-3, p. 1, Dec. 2020. DOI: 10.34385/proc.63.G1-3

5. [5] G. Turin, “An introduction to matched filters,” IRE Transactions on Information Theory, vol. 6, no. 3, pp. 311-329, June 1960. DOI: 10.1109/TIT.1960.1057571

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