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最小二乘支持向量机matlab工具箱1.8版本(Squares support vector machine Toolbox version 1.8)

ECG signal simulation by Matlab using m-code

这是我自己编写的产生PWM波的MATLAB程序，由于PWM波在信号变换领域很有用，希望对大家有所帮助~(This is my own writing production PWM wave of MATLAB, due to the PWM wave in the signal transformation field is very useful, hope to be helpful to you ~ )

说明：  用于潮流和最优潮流计算的最新版本 对于初学者很有用(For optimal power flow calculation of trends and the latest version is useful for beginners)

有关乘积误差模型的估计 检验 最大似然估计值的获取 (MEM model estimation and test)

灰色预测的matlab程序，用于评价问题(Gray prediction matlab program for Evaluation)

Optimized algorithm for nonmagnetic sample characterization

本程序是利用调节参数的方法实现了曲线的局部变化，充分体现了多参数的优越性，通过参数调节实现曲线的局部变化(This procedure is the use of adjustable parameters of the partial realization of the curve changes, fully embodies the advantages of multi-parameter, parameter adjustment achieved through changes in the local curve)

雷达数据处理对于观测的目标位置数据（称为点迹）进行滤波处理，自动形成航迹，并且可以对下一个目标的位置进行估计预测。利用最小二乘算法（LMS）进行滤波处理，得到了比较稳定的航迹估计。 最小二乘方法是参数估计中一种较为常见的参数估计方法。对于雷达观测数据，在我们假定已经精确知道航迹的运动学模型之后，通过建立观测方程，即可以对于模型的参数，如初速度，初始位置和加速度等进行最小均方误差估计。采用序贯最小二乘的方法可以对观测数据进行实时处理，已对待估计参数进行实时更新，然后利用观测模型可以对 数据进行滤波计算。(Radar data processing for target position data observed (known as trace points) filter processing, automatic track, and can be estimated to predict the position of the next target. Using the least squares algorithm (LMS) filtering process, have been relatively stable track estimates. Least-squares parameter estimation method is a more common parameter estimation method. For radar data, we assume that the kinematic model has been accurately track after, through the establishment of observation equations, which can be the parameters of the model, as ever speed, acceleration, etc. initial position and minimum mean square error estimation. Sequential least squares method using the observed data can be processed in real time, has been to treat the estimated parameters are updated in real time, and then use observational data can be filtered model calculations.)

Digitals filters. Passby filters, lowpass and highpass filters.