正则化图像恢复是条件约束的最优化问题，而小波系数的贝叶斯统计选择是基于图像的随机场观点。
A regularized image restoration is the optimization for some conditional constraint, and the selection of wavelet coefficients based Bayesian statistic is on the image random field view.
基于贝叶斯证据框架下的最小二乘小波支持向量机，设计了一种新型模拟电路故障诊断方法。
Based on least squares wavelet support vector machines (LS-WSVM) within the Bayesian evidence framework, a systematic method for fault diagnosis of analog circuits was proposed.
图像的小波系数具有很强的非高斯统计特性，可以建立推广的拉普拉斯先验分布，用贝叶斯估计对图像小波系数滤波来达到降噪目的。
The wavelet subband coefficients of images have highly non Gaussian statistics that may be modeled with generalized Laplacian distributions, and Bayesian estimation is used to suppress noise.
应用推荐