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The present LS-SVMlab toolbox contains Matlab/C implementations for a number of LS-SVM algorithms. (The present LS-SVMlab toolbox contains Ma tlab/C implementations for a number of LS-SVM a lgorithms.)

说明：  反距离权重法主要依赖于反距离的幂值，幂参数可基于距输出点的距离来控制已知点对内插值的影响。(The inverse distance weight method mainly depends on the power value of the inverse distance, and the power parameter can control the influence of known points on the interpolation based on the distance from the output point.)

一个用matlab编写的智能控制源程序。自动生成图像。(An intelligent control with source code written in matlab. Automatically generated image.)

这是基于matlab的信号系统实验程序，可以完成信号系统课程的相关实验，提高信号系统课程的认识和理解。(This is based on the signaling system matlab experimental procedure, you can complete courses related experiments signaling system, improve the signal system course knowledge and understanding.)

炮弹发射视为斜抛运动，已知初始速度为200m/s，问要击中水平距离360m、垂直距离160m的目标，当忽略空气阻力时，发射角应多大？此时炮弹的运行轨迹如何？(Projectile launch angle problem )

mlvessel is a Matlab package for retinal vessel segmentation. The package can be used in two different manners: through the graphical user interface or through script invocation. Use through script invocation relies on input files and produces both file and html output. You may also download a stand-alone executable corresponding to the graphical user interface at our website mentioned below, though some functionalities are only available through script invocation.

基于动量叶素理论的风力机翼型优化，程序为MATLAB编写(Optimization of wind turbine airfoil)

智能优化算法标准测试函数，cec09动态问题测试函数(Benchmark Generator for CEC 2009 Competition on Dynamic Optimization)

spxy，用于校正集验证集划分，基于X、Y矩阵的校正集及验证的划分(Correction set verification set partition)

该算法用于自回归输入模型，是一种迭代的算法。其基本思想是基于对数据先进行一次滤波处理，后利用普通最小二乘法对滤波后的数据进行辨识，进而获得无偏一致估计。但是当过程的输出信噪比比较大或模型参数较多时，这种数据白色化处理的可靠性就会下降，辨识结果往往会是有偏估计。数据要充分多，否则辨识精度下降。模型阶次不宜过高。初始值对辨识结果有较大影响。(The algorithm used for autoregressive input model, it is a kind of iterative algorithm. The basic idea is based on data to conduct a filtering processing, after using ordinary least square method to identify the data filter, and then obtain unbiased consensus estimates. But when the process output signal-to-noise ratio is larger or model parameters are too, this kind of data white processs reliability will drop, identification results tend to be biased estimate. Data should fully, otherwise the identification accuracy down. Model order time shoulds not be too high. Initial value to identification results have great influence on.)