The Inverse Problem of Positive Autoconvolution

We pose the problem of approximating optimally a given nonnegative signal with the scalar autoconvolution of a nonnegative signal. The I-divergence is chosen as the optimality criterion being well suited to incorporate nonnegativity constraints. After proving the existence of an optimal approximatio...

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Bibliographic Details
Published in:	IEEE transactions on information theory Vol. 69; no. 6; pp. 4081 - 4092
Main Authors:	Finesso, Lorenzo, Spreij, Peter
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.06.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	alternating minimization Approximation Approximation algorithms Asymptotic properties Autoconvolution Behavioral sciences Convergence Convolution Divergence I-divergence inverse problem Inverse problems Iterative algorithms Iterative methods Minimization Optimality criteria Optimization positive system Signal processing algorithms
ISSN:	0018-9448, 1557-9654
Online Access:	Get full text
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