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部分APG算法解决了核函数相关模式识别问题的例子，可加速迭代进程，减少运算时间.(An Accelerated Proximal Gradient Algorithm for Nuclear Norm Regularized Least Squares problems)

可以描述光子周期晶格的matlab程序源代码(Photonic lattice can describe the cycle of the source code matlab)

经典微粒群算法MATLAB程序，通过修改w值使得微粒群搜索在全局搜索与局部搜索之间达到一个较好的平衡(Classical PSO MATLAB program, by modifying the value of w makes particle swarm search in the global search and local search to achieve a better balance between)

ANFIS sample code, simulation in matlab.

一个对于光孤子的编程。程序比较简单，但是结果比较实际，推荐。(For the programming of a soliton. Procedure is simple, but the results more practical recommendation.)

Designing a bandpass and bandstop filter using matlab.

用两种向量化和一种循环的思路计算水仙花数，并给出所需时间比较 水仙花数是指一个三位数,其各个数的立方和等于该数(Quantified in two and a loop to the idea of calculating the number of daffodils and narcissus are given the time required for comparison is a three-digit number, the individual cubes, and equal to the number of)

：探索一种能有效抑制和消除颅脑MRI运动伪影产生的方法，以提高图像质量和工作效率。方法：利用包装CT管球的海绵，设计并制作了2 cm x 7．5 cm x 22 cm，3 cm x 7．5 cm x 22 cm，4 cm×7．5 cm x 22 em等3种规格的海绵垫， 配合使用颅脑正交线圈进行颅脑MRI检查。结果：采用“加垫法”行颅脑MRI检查2 638例。其中，一次性扫描成功2 633 例(占99．81％)，失败5例(占0．19％)； 在扫描失败的5例患者中，第2次扫描时配合使用医用绷带成功4例。失败l例。结论：采用“加垫法”行常规颅脑MRI扫描，方法简单、可靠。可有效抑制和消除运动伪影的产生，提高图像质量和工作效率。(To explore a brain can effectively inhibit and eliminate motion artifacts of MRI approach to improve the image quality and efficiency. Methods: The CT tube packing sponge ball, designed and made 2 cm x 7.5 cm x 22 cm, 3 cm x 7.5 cm x 22 cm, 4 cm × 7.5 cm x 22 em 3 sizes, etc. sponge pad, with the quadrature head coil using brain MRI. Results: The " plus cushion Law" the Brain MRI examination 2 638 cases. Among them, the one-time scan is successful 2 633 cases (99.81 ), failed in 5 cases (0.19 ) Conclusion: " plus cushion Law" routine brain MRI scan, the method is simple and reliable. Can effectively suppress and eliminate motion artifacts, and to improve image quality and efficiency.)

说明：  文章叙述了VC++和matlab之间的接口，是用他们同时开发一个项目的好文章(The article describes the VC++ And the interface between matlab, is to use them to develop a project at the same time a good article)

rgb to grayscale conversion very easy very simple check it yourselg its easy and compileable