Approximate message passing (AMP) is an iterative signal recovery algorithm for compressed sensing (CS) applications. In this letter, we present an integral-based orthogonal AMP (IB-OAMP) technique that avoids the requirements of AMP (and also the original form of OAMP) on differentiable and separable denoisers. The orthogonality in IB-OAMP can be established using a Monte Carlo method similar to the training stage in a machine-learning algorithm. These features make IB-OAMP attractive to be used in conjunction with some well-studied denoising algorithms.

中文翻译：

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基于积分的正交AMP方法

近似消息传递（AMP）是用于压缩传感（CS）应用程序的迭代信号恢复算法。在这封信中，我们提出了一种基于积分的正交AMP（IB-OAMP）技术，该技术避免了可微分和可分离降噪器对AMP的要求（以及OAMP的原始形式）。可以使用类似于机器学习算法中训练阶段的蒙特卡洛方法来建立IB-OAMP中的正交性。这些功能使IB-OAMP具有吸引力，可以与一些经过充分研究的降噪算法结合使用。