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说明：  提供迭代算法的matlab实现以及c的实现(iteration )

级联样式表可以使人更能有效地控制网页外观。使用级联样式表，可以扩充精确指定网页元素位置，外观以及创建特殊效果的能力。(Cascading Style Sheets can make more effective control of page appearance. Use cascading style sheets, page elements can be expanded accurately specify the location, appearance and ability to create special effects. )

How to draw bode plots this is a quite good stuff

极化码研究论文 仿真 分析 编码 解码 原理介绍 背景介绍 (Polarization code simulation analysis research paper describes the principles codec Background)

用来计算地球表面两点之间的距离，该程序通过输入两点的经纬度坐标确定两点的距离，可用于各种工程应用当中(The Earth s surface used to calculate the distance between two points, two points in the program by entering the latitude and longitude coordinates to determine the distance between two points can be used in a variety of engineering applications which)

MIMO-OFDM的matlab程序，包括接收和发送部分，采取了简化的信道模型。(the matlab program code for MIMO-OFDM, including the transmission and receiving model.it adopts a simple channel model)

Optimization methods using matlab

LMS及LMSNewton算法的比较。性能表面的等高线(the different between LMS and LMSNewton.)

ballon sanke的matlab实现，可用于图像分割和边缘检测(ballon sanke realize the matlab can be used for image segmentation and edge detection)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数(Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters numerical experiment, this is the modern scientific computing of the answer above problem sets)