paper-with-me

홈 › Papers

ADMM-DAD net: a deep unfolding network for analysis compressed sensing

2021-10-13 · Vasiliki Kouni, Georgios Paraskevopoulos, Holger Rauhut, George C. Alexandropoulos

In this paper, we propose a new deep unfolding neural network based on the ADMM algorithm for analysis Compressed Sensing. The proposed network jointly learns a redundant analysis operator for sparsification and reconstructs the signal of interest. We compare our proposed network with a state-of-the-art unfolded ISTA decoder, that also learns an orthogonal sparsifier. Moreover, we consider not only image, but also speech datasets as test examples. Computational experiments demonstrate that our proposed network outperforms the state-of-the-art deep unfolding network, consistently for both real-world image and speech datasets.

📄 PDF Abstract BibTeX arXiv:2110.06986

Code (1)

vicky-k-19/ADMM-DAD 공식 구현 pytorch

Tasks

compressed sensingDecoder

Methods 이 논문이 사용한 방법론

Test 설명 없음
ADMM The alternating direction method of multipliers (ADMM) is an algorithm that solves convex optimization problems by breaking them into smaller pieces, each of which are…

Similar Papers 제목 키워드 기반

Generalization analysis of an unfolding network for analysis-based Compressed Sensing

2023-03-09 · Vicky Kouni, Yannis Panagakis

Unfolding networks have shown promising results in the Compressed Sensing (CS) field. Yet, the investigation of their generalization ability is still in its infancy. In this paper, we perform a generalization analysis of…

compressed sensingDecoder

Physics-Aware Linearized ADMM and Its Unrolling

2026-06-01 · Satoshi Takabe, Shunta Arai, Tadashi Wadayama arxiv

Recently, partial differential equations (PDEs) have been used to directly model the measurement process in signal processing, although their evaluation is costly. In this paper, we propose a novel alternating direction …

Image Restoration

DECONET: an Unfolding Network for Analysis-based Compressed Sensing with Generalization Error Bounds

2022-05-14 · Vicky Kouni, Yannis Panagakis

We present a new deep unfolding network for analysis-sparsity-based Compressed Sensing. The proposed network coined Decoding Network (DECONET) jointly learns a decoder that reconstructs vectors from their incomplete, noi…

compressed sensingCompressive SensingDecoder

Asymptotic Performance Prediction for ADMM-Based Compressed Sensing

2020-09-17 · 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 unknown structured signal from its underd…

compressed sensingPrediction

Physics-guided Deep Unfolding Network for Enhanced Kronecker Compressive sensing

2025-08-13 · Gang Qu, Ping Wang, Siming Zheng, Xin Yuan arxiv

Deep networks have achieved remarkable success in image compressed sensing (CS) task, namely reconstructing a high-fidelity image from its compressed measurement. However, existing works are deficient inincoherent compre…

Compressive Sensing