鉴于此，必须采用正则化方法，本文中选用的是截断奇异值分解，其正则化参数用l -曲线准则来确定。
In this thesis, we choose truncated singular value decomposition to solve the resulting matrix equations, while the regularization parameter of TSVD is determined by the L-curve criterion.
在理想状态下，假定火源为线火源，采用离散正则化方法对矿井隐蔽线火源进行反演。
Under the perfect condition, supposes fire as line fire, applying discrete regularization method into the inversion of coal mine concealed fi.
为了获得稳定而满意的解，我们采用直方图约束下的正则化方法对连续近似迭代进行约束。
To obtain a stable solution, in our method, successive approximation process is constrained by prior histogram and laplacian regularization.
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。
Dense sample data are acquired by using numerical control platform of high precision, and the Bayesian generalization is adopted during training the neural network.
文中采用贝叶斯正则化与BP网络结合的方法，建立动态前馈校正模型。
This paper establishes dynamic forward feedback correction model with the method of combining Bayes regularization and BP neural network.
采用频域正则化求逆和小波域维纳滤波去噪的方法对已知线性降晰模型的含噪图像进行图像复原。
Image is restored which is blurred by the known linear model and noise, with the method of frequency-domain regularized inversion and wavelet-domain wiener filter denoising.
基于相空间重构的非线性预报思想，建立一个时滞的BP神经网络模型，采用贝叶斯正则化方法提高BP网络的泛化能力。
Based on nonlinear prediction ideas of reconstructing phase space, this paper presents a time delay BP neural network model, whose generalization is improved utilizing Bayes' regularization.
本文采用的是辅助边界条件方法(ABC方法)，或者非局部正则化方法。
The Auxiliary Boundary Condition method (ABC method) or non-local regularization method is used in this thesis.
文中采用贝叶斯正则化与BP网络结合的方法，建立动态前馈校正模型。
The BPNN model of Bayesian regularization method was adopted to create the adaptivity and generalization of BPNN.
前者多采用了正则表达式的描述方法，偏向于传统的结构化的查询方式，能够清楚的表述用户的查询意图；
The former one takes advantage of regular expressions as traditional queries and could expose users's need easily.
前者多采用了正则表达式的描述方法，偏向于传统的结构化的查询方式，能够清楚的表述用户的查询意图；
The former one takes advantage of regular expressions as traditional queries and could expose users's need easily.
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