Gmr.m-(NMR-a-MRI-Properties)

MATLAB是美国MathWorks公司出品的商业数学软件，用于算法开发、数据可视化、数据分析以及数值计算的高级技术计算语言和交互式环境，主要包括MATLAB和Simulink两大部分。(MATLAB is a very popular language for technical computing used by students, engineers, and scientists in universities, research institutes, and industries all over the world.)

光线追击程序，可以对光线的传播行为进行仿真，功能强大，绘图精美，将安装包放在MATLAB子目录下并进行相应设置即可使用。(Raytracing program, you can simulate the propagation of light, powerful, beautiful graphics, the package will be installed on the MATLAB subdirectory and make the appropriate settings to use.)

盲均衡中的常模算法用于抽样判决后的多径效应均衡，显著降低误码率(Multipath equalization Blind equalization algorithm norm for post-judgment sampling, significantly reduce the error rate)

这些文件夹里面包含着卷积码、调制、加高斯白噪声的程序、多径衰落径道的程序。。对那些初学者是很有帮助的。。。(The folder contains a convolutional coding, modulation, plus Gaussian white noise process, multi-path channel fading process. . Is very helpful for those beginners. . .)

说明：  实现小波数字水印，比较简单 采用量化数组嵌入(The realization of wavelet digital watermarking, is relatively simple to quantify the use of embedded array)

采用线性滤波法即AR法模拟脉动风速,计算时间短，模拟效果好(Linear filtering AR simulation fluctuating wind speed)

基于矩量法的二维金属体散射程序，内含基本原理的介绍，matlab程序在附录(Method of Moments Based on the two-dimensional metal body scattering process, includes introduction to basic principles, matlab program in Appendix)

This program performs canny edge detection. (MATLAB code)

用各种尺寸的掩模平滑图像,matlab源代码(Mask of all sizes with a smooth image, matlab source code)

拟牛顿法和最速下降法(Steepest Descent Methods)一样只要求每一步迭代时知道目标函数的梯度。通过测量梯度的变化，构造一个目标函数的模型使之足以产生超线性收敛性。这类方法大大优于最速下降法，尤其对于困难的问题。另外，因为拟牛顿法不需要二阶导数的信息，所以有时比牛顿法(Newton s Method)更为有效。如今，优化软件中包含了大量的拟牛顿算法用来解决无约束，约束，和大规模的优化问题。(The quasi-Newton method and the Steepest Descent Methods only require that each step iterations know the gradient of the objective function. By measuring the change of the gradient, constructing a model of the objective function is sufficient to produce superlinear convergence. This method is much better than the steepest descent method, especially for difficult problems. In addition, because the quasi-Newton method does not require information on the second derivative, it is sometimes more effective than the Newton s Method. Today, the optimization software contains a large number of quasi-Newton algorithm used to solve the unconstrained, constraint, and large-scale optimization problems.)