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概率振幅和频率解调

Probabilistic amplitude and frequency demodulation
课程网址: http://videolectures.net/nips2011_turner_amplitude/  
主讲教师: Richard Turner
开课单位: 伦敦大学学院
开课时间: 2012-09-06
课程语种: 英语
中文简介:
许多最近的科学和工程问题要求信号被分解成缓慢变化的正包络和快速变化的载波的乘积,其瞬时频率也随时间缓慢变化。尽管信号处理提供了用于所谓的幅度和频率解调(AFD)的算法,但是所有现有方法都存在众所周知的问题。由于AFD不适合这一事实,我们使用概率推理来解决问题。这种新方法称为概率幅度和频率解调(PAFD),使用von Mises分布的自回归推广来模拟瞬时频率,并使用具有积极约束的高斯自回归动力学对包络进行建模。一种新颖的期望传播形式用于推理。我们证明了尽管PAFD在计算上要求很高,但它在干净,嘈杂和缺失的数据设置中优于以前的合成和实际信号方法。
课程简介: A number of recent scientific and engineering problems require signals to be decomposed into a product of a slowly varying positive envelope and a quickly varying carrier whose instantaneous frequency also varies slowly over time. Although signal processing provides algorithms for so-called amplitude- and frequency-demodulation (AFD), there are well known problems with all of the existing methods. Motivated by the fact that AFD is ill-posed, we approach the problem using probabilistic inference. The new approach, called probabilistic amplitude and frequency demodulation (PAFD), models instantaneous frequency using an auto-regressive generalization of the von Mises distribution, and the envelopes using Gaussian auto-regressive dynamics with a positivity constraint. A novel form of expectation propagation is used for inference. We demonstrate that although PAFD is computationally demanding, it outperforms previous approaches on synthetic and real signals in clean, noisy and missing data settings.
关 键 词: 瞬时频率; 振幅; 频率解调; 用概率推理问题
课程来源: 视频讲座网
最后编审: 2020-06-08:wuyq
阅读次数: 28