论文标题
信号从傅立叶大小
Signal Inpainting from Fourier Magnitudes
论文作者
论文摘要
信号介绍是在信号中恢复降解或丢失样品的任务。在本文中，当观察到傅立叶大小时，我们解决了信号介入。我们提出了一个问题的数学表述，突出了其与相位检索的联系，并介绍了两种解决该问题的方法。首先，我们得出了一种交替的最小化方案，该方案与Gerchberg-Saxton算法（一种经典的阶段检索方法）共享相似之处。其次，我们提出了对问题的放松，这是受到最新方法的启发，这些方法将相位的阶段检索重新调整为半决赛程序。我们评估了这些方法在语音信号中填充差距的任务的潜力。我们的方法既表现出恢复原始信号和稳健性到幅度噪声的高可能性。
Signal inpainting is the task of restoring degraded or missing samples in a signal. In this paper we address signal inpainting when Fourier magnitudes are observed. We propose a mathematical formulation of the problem that highlights its connection with phase retrieval, and we introduce two methods for solving it. First, we derive an alternating minimization scheme, which shares similarities with the Gerchberg-Saxton algorithm, a classical phase retrieval method. Second, we propose a convex relaxation of the problem, which is inspired by recent approaches that reformulate phase retrieval into a semidefinite program. We assess the potential of these methods for the task of inpainting gaps in speech signals. Our methods exhibit both a high probability of recovering the original signals and robustness to magnitude noise.
