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| 005 | 20220823110753.0 |
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| 245 | 12 | $a A fast algorithm for spatiotemporal signals recovery using arbitrary dictionaries with application to electrocardiographic imaging / $c S. F. Caracciolo ... [et al.]. |
| 490 | 0# | $a Trabajos publicados del IAR ; $v no. 1686 |
| 520 | ## | $a This paper presents a method to solve a linear regression problem subject to group lasso and ridge penalisation when the model has a Kronecker structure. This model was developed to solve the inverse problem of electrocardiography using sparse signal representation over a redundant dictionary or frame. The optimisation algorithm was performed using the block coordinate descent and proximal gradient descent methods. The explicit computation of the underlying Kronecker structure in the regression was avoided, reducing space and temporal complexity. We developed an algorithm that supports the use of arbitrary dictionaries to obtain solutions and allows a flexible group distribution. |
| 773 | 0# | $7 ||as $t Biomedical Physics and Engineering Express $x 2057-1976 $g Vol. (2022). p. |
| 700 | 1# | $a Caracciolo, Santiago Federico. |
| 700 | 1# | $a Caiafa, Cesar F. |
| 700 | 1# | $a Martínez Pería, Francisco Dardo. |
| 700 | 1# | $a Arini, Pedro David. |
| 653 | ## | $a CGI, Group Lasso, Kronecker Product, Sparse Regularization. |
| 040 | ## | $a AR-BaBIR |
| 856 | ## | $u https://iopscience.iop.org/article/10.1088/2057-1976/ac835b $y Web |
| 856 | ## | $u https://www.iar.unlp.edu.ar/biblio/htdocs/artic/contri/1686.pdf $y PDF |