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.

翻译：在本文中,我们基于ADMM分析压缩遥感的算法,提出了一个新的深层正在发展的神经网络。提议的网络联合学习了多余的分析操作员进行封闭,并重建了感兴趣的信号。我们比较了我们提议的网络与最新开发的ISTA解码器,该解码器也学习了正方形解码器。此外,我们认为,不仅图像,而且还将语音数据集作为试验例子。计算实验表明,我们提议的网络比最新的深层开发网络更完善,对于真实世界的图像和语音数据集来说都是一致的。