正则化

• Dense sample data are acquired by using numerical control platform of high precision , and the bayesian generalization is adopted during training the neural network
  通过高精度的数控移动工件台获取密集的样本数据，并在神经网络训练过程中采用贝叶斯正则化方法。
• For the first time the tikhonov " s regularizing method is used to solve the failure rate of the products of electrical engineering when their failure distribution is unknown
  当电工产品的失效分布类型未知时，首次利用求解不适定问题的正则化方法来求解其失效率。
• Mundy j l , zisserman a eds . , mit press , cambridge , mass . , 1992 , pp . 375 - 497 . 15 rothe i , susse h , voss k . the method of normalization to determineinvariants
  不幸的是，即使我们计算出我们的相关函数的这些新的矩，我们也无法分离出光照的影响，因为这些仿射正则化矩是实值的。
• A regularized strategy which is based on the gauss kernel is recommened , and the discrepancy principle to select the regularized parameter is proved
  摘要以正则化思想为基础，介绍了基于高斯核来构造正则算子的方法，使其对噪音进行过滤，并证明了类似于正则化方法中选择参数的偏差原理。
• 3 ) this thesis proposed a regularized kernel recursive least square ( rkrls ) algorithm . the coefficients and error of rkrls model are gotten and the generalization ability is analyzed
  3 )对递推最小二乘进行非线性的kernel变换，并采用正则化技术改写了目标函数，提出了一种rkrls算法。
• 1 ) the basic theories used in this thesis were introduced , including machine learning , kernel machine , statistical learning theory and regularized theory
  介绍了机器学习和kernel学习机基本理论。介绍了kernel算法的通用结构、 mercer定理及映射函数。介绍了统计学习理论和正则化网络的理论。
• The numerical simulations demonstrate the convergency within a wide region of this method to out - perform the conventional regularization gauss - newton method
  通过与传统的正则化高斯牛顿法相比较，显示了小波多尺度法是一个大范围收敛、能够有效节省计算量的方法，数值模拟的结果也表明了方法的有效性。
• Secondly , to perfect the known restoring models , a new space - adaptive regularization model of image restoration is constructed by redesigning regularized parameter and regularized item
  第二,在现有复原模型的完善上,重新构建正则化参数与正则化项,构造了新的具有空间自适应性质的正则化图像复原模型。