Complex Trainable Ista for Linear and Nonlinear Inverse Problems
Satoshi Takabe, Tadashi Wadayama, Yonina C. Eldar
Abstract
Complex-field signal recovery problems from noisy linear/nonlinear measurements appear in many areas of signal processing and wireless communications. In this paper, we propose a trainable iterative signal recovery algorithm named complex-field TISTA (C-TISTA) which treats complex-field nonlinear inverse problems. C-TISTA is based on the concept of deep unfolding and consists of a gradient descent step with the Wirtinger derivatives followed by a shrinkage step with a trainable complex-valued shrinkage function. Importantly, it contains a small number of trainable parameters so that its training process can be executed efficiently. Numerical results indicate that C-TISTA shows remarkable signal recovery performance compared with existing algorithms.
BibTeX
@inproceedings{icassp2020_complextrainable,
title = {Complex Trainable Ista for Linear and Nonlinear Inverse Problems},
author = {Satoshi Takabe and Tadashi Wadayama and Yonina C. Eldar},
booktitle = {ICASSP 2020},
year = {2020}
}