标题： 通过凸优化从幅度光谱图估计信号 显示英文标题

标题： Estimating a Signal from a Magnitude Spectrogram via Convex Optimization

摘要： 从短时傅里叶变换（STFT）的幅度恢复信号的问题在音频信号处理中是一个长期存在的问题。现有的方法依赖于启发式算法，由于问题的非凸性，这些算法通常表现不佳。我们引入了该问题的一种表述，使其适合于可处理的凸规划程序。我们观察到，我们的方法比标准的Griffin-Lim算法能获得更好的重建效果。我们提供了算法并讨论了实际实现的细节，包括如何使该方法扩展到更大的例子上。 显示英文摘要

摘要： The problem of recovering a signal from the magnitude of its short-time Fourier transform (STFT) is a longstanding one in audio signal processing. Existing approaches rely on heuristics that often perform poorly because of the nonconvexity of the problem. We introduce a formulation of the problem that lends itself to a tractable convex program. We observe that our method yields better reconstructions than the standard Griffin-Lim algorithm. We provide an algorithm and discuss practical implementation details, including how the method can be scaled up to larger examples.