ua4_1

说明：  用优化算法求解运输问题。 1.不使用linprog，比较歧异解 2.用西北角法求初始基本可行解，用闭回路法确定退出基和更新运输矩阵 3.不能处理非平衡的运输问题(Optimization algorithm used to solve transport problems. 1. Do not use linprog, compare differences solution 2. With the northwest corner of France seeking an initial basic feasible solution, using closed-loop method to determine the transport out of the base and update the matrix 3. Can not handle the transport of non-equilibrium)

J2T_reward_points_1_6 magento 最实用的分销积分插件(J2T_reward_points_1_6 Give your store an incentive points-based loyalty system with J2T Points &... J2T Reward Points+ Referral program )

This function is easy to use, logical, and does exactly what it says it will. I am very happy with it.

两种目标类型有无脉冲积累的SNR相对检测距离的大小(Detection range With 7-pulse NCI and Single pulse)

i am in need 4g related matlab code.i learning in area of lte-advanced downlink for writing the matlab code

file program berkeleye university

基于正则化转置的LDA matlab源代码，可以应用在人脸识别中，详细说明见readme(based Regularization home to the LDA Matlab source code, can be applied to face recognition, detailed explanation see readme)

说明：  wiener filtering, improving speech, speech recognition

用matlab读取PGM格式图片，简单易懂，参考性强(Matlab read the PGM format picture, straightforward reference)

实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。 对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。 深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。 利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。 (SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification.)