论文标题
本地固定信号的时间尺度合成
Time-scale synthesis for locally stationary signals
论文作者
论文摘要
我们为局部固定信号的建模开发了一种基于时间尺度的概率方法。受我们以前的工作的启发，该模型涉及零均值的复杂高斯小波系数，其分布随时间依赖于比例轴的时间而变化。在最大的后验方法中，我们提出了模型参数的估计器，即时变刻度平移和基础功率谱。提出的方法在一个denoising示例中进行了说明。还表明该模型可以处理具有快速变化的本地固定信号，并且在这种情况下提供的非常尖锐的时间尺度表示形式比同步的小波或重新分配小波变换更加集中。
We develop a timescale synthesis-based probabilistic approach for the modeling of locally stationary signals. Inspired by our previous work, the model involves zero-mean, complex Gaussian wavelet coefficients, whose distribution varies as a function of time by time dependent translations on the scale axis. In a maximum a posteriori approach, we propose an estimator for the model parameters, namely the time-varying scale translation and an underlying power spectrum. The proposed approach is illustrated on a denoising example. It is also shown that the model can handle locally stationary signals with fast frequency variations, and provide in this case very sharp timescale representations more concentrated than synchrosqueezed or reassigned wavelet transform.
