IEICE Communications Express
Online ISSN : 2187-0136
ISSN-L : 2187-0136
Special Cluster in Conjunction with IEICE General Conference 2022
Deconvolution ISTA: A solver for multidimensional convolution problems with low computational complexity
Masanori Gocho
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2022 Volume 11 Issue 12 Pages 784-790

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Abstract

In this report, we employ the iterative shrinkage-thresholding algorithm (ISTA), which is one of the sparse reconstruction methods, to solve multidimensional circular convolution problems. The novelties of this work are as follows: the derivation of the subgradient and the Lipschitz constant of a multidimensional deconvolution problem;the construction of a sparse reconstruction algorithm to solve the problem;the evaluation of the qualitative ability of the algorithm, especially computational complexities. The proposed method can not only solve the convolution problems but also achieve low computational complexity.

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© 2022 The Institute of Electronics, Information and Communication Engineers
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