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pattern-recognition
- 模式识别的内容,包括模式识别的基本概念、模式识别方法及应用。具体的内容包括:正则化网络、Bayes决策理论、分类器组合、统计学习理论、概率密度估计、非监督学习方法-Pattern recognition, including the basic concepts of pattern recognition, pattern recognition methods and applications.Specific content, including: Regularization Netwo
regu
- 正则化算法的matlab程序,采用Tiknov标准方法计算反问题的程序-Regularization algorithm matlab program, using the program Tiknov standard method to calculate the inverse problem
Bayes-in-BP(code)
- 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。-Use Bayes to train BP network
adaptive_regularization
- 代码给出了数字图像处理图像复原运算方法中的自适应滤波、正则化滤波、盲去卷积滤波等滤波方法的实现过程,经matlab调试运行成功,效果明显-Code gives a computing method of digital image processing image restoration, adaptive filtering, regularization filter, blind go convolution filtering and other filtering methods to
FFD4D
- 一种基于正则化总变图像处理方法,很好,值得研究此方面的朋友研究-Based on the image processing method for total variation regularization, good, worthy of study in this regard friends
function1111
- 一种基于TV正则化的自适应图像去模糊方法:最小优化算法-Based on TV regularization adaptive image deblurring method: Minimal Optimization
demoBagSVM
- 一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章:Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。-A semi-supervised SVM is presented for the classification of remote sensing images. The
gcv
- 广义交叉验证函数(GCV) 广义交叉验证函数是用随机的方法对于一个给定的值A的正则化参数的计算。-Generalized cross-validation function (GCV) generalized cross validation function is stochastic method for a given value A regularization parameter calculations.
BP_LM
- 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 -Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, namely LM optimization algorithm (trainlm) and Baye
DRLSE_v0
- 本程序包采用距离正则化的水平集的方法,对多种图像进行处理和分割,实验结果表明,分割结果比传统水平集方法好很多-This package uses the distance regularized level set method, a variety of image processing and segmentation, experimental results show that the segmentation result is much better than the traditi
beiyesizhengzehua
- 采用贝叶斯正则化算法提高 BP 网络的推广能力,采用两种训练方法-Bayesian regularization algorithm to improve the generalization ability of BP network, using two training methods
code
- 自适应选择正则化参数和范数的非盲图像复原方法,效果真心不错。-Select the non-blind adaptive image restoration method parameters and norm regularization, the effect really good.
GISA
- 一种求解lp范数正则化约束的稀疏表示方法-Sparse representation method for solving LP norm regularization constraint
mrics
- 代码的mrics。M’是从他们的傅立叶系数的一个子集,使用总变分正则化图像重建的分裂Bregman方法的实现。使用代码指令可以在文件“mrics顶在评论中发现。”。一个演示脚本也包括在内,显示正确的使用方法。-The code ‘mrics.m’ is an implementation of the Split Bregman method for reconstructing images a subset of their Fourier coefficients using total
AOS-method
- 正则化P-M模型的半隐式求解格式,加性分裂算子(AOS)方法-Regularization P- semi implicit solving format of M model, additive division operator (AOS) method
Distance-Regularized-Level-Set
- 水平集方法是一种先进的图像分割方法。这个matlab代码演示了一个基于边缘的活动轮廓模型,是下面一篇带距离正则化的水平集方程论文的应用: C. Li, C. Xu, C. Gui, M. D. Fox, Distance Regularized Level Set Evolution and Its Application to Image Segmentation , IEEE Trans. Image Processing, vol. 19 (12), pp. 3243-3254,
l_curve
- 反演问题中正则化参数阿尔法的l-curve选取方法,用于画出l-curve,选取曲率最大的点。-Inverse problem regularization parameter alpha l-curve selection method used to draw l-curve, the point of maximum curvature.
bp2
- 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。-Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, na
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
compressed-sensing_OPM
- 正交匹配追踪算法每次迭代均只选择与残差最相关的一列,自然人们会想:“每次迭代是否可以多选几列呢?”,正则化正交匹配追踪(RegularizedOMP)就是其中一种改进方法。本篇将在上一篇《压缩感知重构算法之正交匹配追踪(OMP)》的基础上给出正则化正交匹配追踪(ROMP)算法的MATLAB函数代码,并且给出单次测试例程代码、测量数M与重构成功概率关系曲线绘制例程代码。-Compressed Sensing