搜索资源列表
0-svnn
- 这段代码实现了一个新的MLP神经网络训练方法,来自论文A new method for neural network regularization（内附）-This code implements a new training method for MLP neural networks, named Support Vector Neural Network (SVNN), proposed in the work: O. Ludwig “Study on Non-parametric Me
thmogenr
- resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the radio-frequency coils or to problems associated with the acquisition sequences
Tikhonov_regularization_toolbox
- Tikhonov正则化工具箱，可实现病态方程组的正则化，以及采用L曲线法、岭估计法、GCV法等确定正则化参数，内含使用方法，亲测有效。-Tikhonov regularization toolbox, which can realize regularization in morbid equations, and using the L curve method, ridge estimation, GCV method to determine the regularization para
sunsal
- 稀疏中的基于加权L1正则化的SUNSAL算法-The sparse based on weighted L1 regularization algorithm SUNSAL
L_CURVE
- 利用L曲线来确定正则化参数的程序，L曲线来确定正则化参数-Use L curve to determine the regularization parameters of the program，L curve to determine the regularization parameters
Regularize
- 压缩感知中ROMP中正则化部分代码,ROMP算法流程中的第二步鉴定与第三部正则化部分-Compression perception ROMP Regularization part of the code
pso-svm-prediction
- 该程序是基于粒子群算法优化支持向量机中的正则化参数C和核函数参数K的算法，实现了对电力负荷的短期预测，预测效果较好，可根据自己要求进行更改。-The algorithm is based on particle swarm optimization algorithm to optimize regularization parameter C and kernel function parameter K in support vector machine. It realizes the s
DSFJKLSDJFKLDSJ
- 通过L曲线确定正则化参数，主要用于磁探测电阻抗中，是我毕设的一部分，可运行。-The L curve is used to determine the regularization parameter, which is mainly used for the magnetic detection electrical impedance.
Reconstructing-Images-Corrupted
- A variational model to denoise an image corrupted by Poisson noise, Like the ROF model the model uses totalvariation regularization, which preserves edges
An-efficient-augmented-
- 基于经典的增广拉格朗日乘子法, 对求解一类带有特定结构（主要是针对凸规划）的非光滑等式约束优化问题, 我们提出、分析并测试了一个新算法. 在极小化增广拉格朗日函数的每一步迭代中, 该算法有效结合了带有非单调线性搜索的交替方向技术, 我们建立了算法的收敛性, 并用它来求解在带有全变差正则化的图像恢复问题.-Based on the classic augmented Lagrangian multiplier method, we propose, analyze and test an algo
Efficient_Image_Dehazing
- Dehazing边界约束以及有效的图像上下文正规化-Efficient Image Dehazing with Boundary Constraint and Contextual Regularization
OVM
- A Dynamical Tikhonov Regularization for Solving Ill-posed Linear Algebraic Systems.pdf，以上论文提出的求解病态线性方程组的一种较新梯度下降法-A Dynamical Tikhonov Regularization for Solving Ill-posed Linear Algebraic Systems.pdf, more than one paper proposes solving ill-conditi
Tikhonov
- 不适定问题的迭代Tikhonov正则化方法，介绍了Tikhonov正则化方法解决不定适问题-An iterative Tikhonov regularization method for ill posed problems is introduced, and the Tikhonov regularization method is introduced to solve the ill posed problem
TVAL3_v1.0
- matlab压缩感知中的一种基于全变分正则化的重建算法——TVAL3-In compressed sensing, a reconstruction algorithm based on total variation regularization- TVAL3
RNLF-master
- 文章源码Adaptive Regularization of the NL-Means:Application to Image and Video Denoising-Adaptive Regularization of the NL-Means: Application to Image and Video Denoising
CSR_Denoising
- 该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）-It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the
bpNeural-network-instance
- 例1 采用动量梯度下降算法训练 BP 网络。 例2 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Example 1 uses the momentum gradient descent algorithm to train the BP network. Example 2 uses the Bayesian
mppliedappliedregularization
- 基于正则化转置的LDA matlab源代码,可以应用在人脸识别中-Based on regularization transposed LDA matlab source code, can be applied in face recognition
INNUXAT9
- 基于正则化转置的LDA matlab源代码,可以应用在人脸识别中-Based on regularization transposed LDA matlab source code, can be applied in face recognition
akplied-coje
- 基于正则化转置的LDA matlab源代码,可以应用在人脸识别中-Based on regularization transposed LDA matlab source code, can be applied in face recognition