基于概率先验的线谱估计
Line Spectrum Estimation with Probabilistic Priors
摘要：
对于线性谱估计，我们推导出最大后验概率估计的先验知识的频率概率建模。由于频谱是周期性的，因此合适的分布是圆形冯米塞斯分布，其可以参数化频率的先验确定性的整个范围。一个有效的交替投影方法被用来解决由此产生的最优化问题。估计数值评估和比较与其他估计和Cramér-Rao界。
英文摘要：
For line spectrum estimation, we derive the maximum a posteriori probability estimator where prior knowledge of frequencies is modeled probabilistically. Since the spectrum is periodic, an appropriate distribution is the circular von Mises distribution that can parameterize the entire range of prior certainty of the frequencies. An efficient alternating projections method is used to solve the resulting optimization problem. The estimator is evaluated numerically and compared with other estimators and the Cramér-Rao bound.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
