1、

Two class methods are con-cluded: regularization based method and labeled data set augmenting based method.

并将其归纳成两大类方法:基于正则化的方法和基于有标注数据样本扩充的方法。

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2、

Based on the relation between sparsity and lk norm, a regularization method is presented for the sparse representation of signals.

本文基于lk范数与稀疏性之间的关系,提出了一种基于lk范数的正则化方法,该方法在抑制信号噪声的同时,实现了信息的高精度稀疏表示。

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3、

Restoration of Turbulence-Degraded Images Based on RL Algorithm with Total Variation Regularization

基于总变分规整化的湍流退化图像复原RL算法

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4、

Secondly, according to the information about the inlets, the COD values of each monitoring point were predicted by NN method successfully, during which the over-fitting problem was solved by Bayesian automatic regularization technology.

其次,根据陆源入海水体的信息,成功地采用神经网络法预测监测站位的COD值,并采用Bayesian自动正则化技术解决了模型的过拟合问题;

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5、

An Image Denoising Method Using Total Variation Regularization for Flow Field

一种全变差正则化流场的图像抑噪方法

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6、

Regularization technique could enhance SAR ( Synthetic Aperture Radar) image by imposing prior information.

正则化方法通过增加先验信息约束,达到增强SAR图像特征的目的。

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7、

Thirdly, the morbid state transform is opposite in the process of the method of LAMBDA, this paper proposed covariance regularization method: in the front of reduction correlation integer transform oppose the covariance Tikhonov regularization, effectively improve the reliability solution of double difference ambiguity.

针对LAMBDA方法出现的病态变换,本文提出协方差阵正则化法:降相关性整数变换前对协方差阵Tikhonov正则化,有效地提高了双差模糊度解算的可靠性,减少解算历元数。

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8、

Firstly, the data-fitting term of TV model is rewrite in Fourier domain and defined on the titling mode adaptive reciprocal cell, thus adaptive reciprocal cell based TV regularization model ( ARCTV) is constructed.

首先将TV模型中的数据保真项定义在斜模式自适应倒易晶胞上,建立了一种基于斜模式自适应倒易晶胞的TV正则化模型。

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9、
10、

Especially for the problem of thin body, duple regularization of both the nearly singular integrals and ill-posed inverse problems is also successful in the two-dimensional boundary element method.

特别对二维薄体位势边界元法,成功实现了几乎奇异积分和不适定反问题的双重正则化。

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11、

A Stable Solution to the Technique for Identifying the Total Parameters ( TITP) of Biological Materials ── Regularization Approach

生物热物性全参数辨识方法(TITP)的稳定求解措施&正则化途径

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12、

This paper proposes a motion equation of the rigid object which moves in the background field. An inversional model which can get wind through the moving object's trajectory is first referred by using the variational adjoint method and Tikhonov regularization principle.

本文首先给出了刚性示踪物在背景流场中的运动方程,利用变分伴随方法结合反问题的正则化思想建立了示踪物轨迹反演背景流场的伴随模型。

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13、

The applicability study of cutting bulk on the single glide plane rock slope regularization

削坡在单滑动面岩质边坡治理中的适用性研究

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14、

Analysis on the Constrained Regularization Inversing CONTIN Algorithm in Particle Sizing

颗粒粒径测量中约束正则CONTIN算法分析

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15、

Self-adaptive mesh generation in electrical capacitance tomography based on total variation regularization algorithm

基于TV正则化算法的电容层析成像自适应剖分方法

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16、

Two Regularization Methods for Solving Bending Moment Field of Classical Beam Problems

求解经典梁弯矩的两种正则化方法遗传算法及正则化在荷载反问题中的应用

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