5 citations · 10 across the 5 of their papers we have counts for
5 papers
Approximate Proximal Operators for Analog Compressed Sensing Using PN-junction Diode
Soma Furusawa, Taisei Kato, Ryo Hayakawa +1
In order to realize analog compressed sensing, the paper considers approximate proximal operators of the and minimax concave penalty (MCP) regularization functions. Specif…
Asymptotics of Proximity Operator for Squared Loss and Performance Prediction of Nonconvex Sparse Signal Recovery
Ryo Hayakawa
Proximal splitting-based convex optimization is a promising approach to linear inverse problems because we can use some prior knowledge of the unknown variables explicitly. An unde…
Noise Variance Estimation Using Asymptotic Residual in Compressed Sensing
Ryo Hayakawa
In compressed sensing, measurements are typically contaminated by additive noise, and therefore, information about the noise variance is often needed to design algorithms. In this…
Asymptotic Performance Prediction for ADMM-Based Compressed Sensing
Ryo Hayakawa
In this paper, we propose a method to predict the asymptotic performance of the alternating direction method of multipliers (ADMM) for compressed sensing, where we reconstruct an u…
Trainable Projected Gradient Detector for Massive Overloaded MIMO Channels: Data-driven Tuning Approach
Satoshi Takabe, Masayuki Imanishi, Tadashi Wadayama +2
This paper presents a deep learning-aided iterative detection algorithm for massive overloaded multiple-input multiple-output (MIMO) systems where the number of transmit antennas $…