arXiv:2512.17426stat.MLcond-mat.dis-nn2025-12被引 1

改进信号重建算法,提升稀疏信号恢复精度。

Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing

  • 基于1RSB消息传递框架设计新算法,优化非凸性控制。
  • 理论与实验均显示重建极限优于传统方法,接近最优性能。
  • 适合研究信号恢复、统计物理与机器学习交叉问题的学者。

本文研究通过平滑截断绝对偏差(SCAD)惩罚进行稀疏信号重构,提出一种一阶复制对称破缺(1RSB)扩展的近似消息传递算法(1RSB-AMP)。从信念传播的1RSB形式出发,推导出1RSB-AMP的显式更新规则及对应的态演化方程(1RSB-SE)。对比显示,1RSB-AMP与1RSB-SE在宏观层面高度一致,即使在复制对称(RS)AMP发散的参数区域也表现良好。1RSB-SE的固定点分析揭示了成功、失败和发散三类相区,其中发散边界受帕里西参数影响。提出以最小化发散区域大小为新准则确定该参数,结合先前研究提出的非凸性控制(NCC)协议,显著提升了算法的完美重建极限。数值求解1RSB-SE及1RSB-AMP实验验证了该极限可实际达成,虽提升有限,仍略低于贝叶斯最优阈值。此外,还报告了重叠、自由熵、复杂度及非自平均关联率等热力学量在1RSB相中的行为特征。

原文摘要 · Abstract (English)

We consider sparse signal reconstruction via minimization of the smoothly clipped absolute deviation (SCAD) penalty, and develop one-step replica-symmetry-breaking (1RSB) extensions of approximate message passing (AMP), termed 1RSB-AMP. Starting from the 1RSB formulation of belief propagation, we derive explicit update rules of 1RSB-AMP together with the corresponding state evolution (1RSB-SE) equations. A detailed comparison shows that 1RSB-AMP and 1RSB-SE agree remarkably well at the macroscopic level, even in parameter regions where replica-symmetric (RS) AMP, termed RS-AMP, diverges and where the 1RSB description itself is not expected to be thermodynamically exact. Fixed-point analysis of 1RSB-SE reveals a phase diagram consisting of success, failure, and diverging phases, as in the RS case. However, the diverging-region boundary now depends on the Parisi parameter due to the 1RSB ansatz, and we propose a new criterion---minimizing the size of the diverging region---rather than the conventional zero-complexity condition, to determine its value. Combining this criterion with the nonconvexity-control (NCC) protocol proposed in a previous RS study improves the algorithmic limit of perfect reconstruction compared with RS-AMP. Numerical solutions of 1RSB-SE and experiments with 1RSB-AMP confirm that this improved limit is achieved in practice, though the gain is modest and remains slightly inferior to the Bayes-optimal threshold. We also report the behavior of thermodynamic quantities---overlaps, free entropy, complexity, and the non-self-averaging susceptibility---that characterize the 1RSB phase in this problem.

信号重建消息传递非凸优化统计物理

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