基于EM算法的最优斜高斯核设计

Optimal Tilted Gaussian Kemel Design Using Expectation Maximization Algorithm

对于采用固定窗或核的时频分布,其适用的信号形式具有很大的局限性。基于信号的核能克服这样的缺点,斜高斯核是其中一类,为了得到基于不同信号的最优斜高斯核,本文提出采用EM算法根据实际信号的模糊函数估计斜高斯核的参数,以达到核的最优设计。

With fixed windows or kernels, Time-frequency representation(TFR)performs well only for limited signals, however representation with signal depended kernels can overcome this limitation. The TFR developed here is based on signal depended tilted Gaussian kernel. In order to find the optimal tilted Gaussian kernel we introduce expectation maximization(EM)algorithm. We can easily get the optimal Gaussian kernel from the estimated parameters of the auto-component by simply transplanting.