sparsemang_delay_modify

Rake reception using matlab

本书全面地介绍了MATLAB的相关内容，是一本很好的入门教程(The book provides a comprehensive introduction to the MATLAB is a good introductory tutorial)

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.)

MATLAB Simulink Conference 2007_Track2-1

matlab实例教程，很多经典的程序实例及代码。(matlab tutorial examples, many of the classic examples of procedures and code.)

《MATLAB神经网络30个案例分析》中的第6个例子，案例6 PID神经元网络解耦控制算法_多变量系统控制。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of 6 examples, case 6 _ multi-variable PID neural network decoupling control algorithm control system. Hope to have certain help to everybody! )

针对离散系统进行开环、闭环分析；绘制Bode、Nyquist、根轨迹图；阶跃、脉冲响应，并均给出响应的图示。(For the discrete system closed loop analysis of ring, open drawing Bode, Nyquist, root locus diagram step, impulse response, and the response of the diagrams are given.)

Simple MultiLevel Inverter Design

对数据集breast_cancer，用LR，NB算法对其进行操作(On the data set breast_cancer, with LR, NB algorithms manipulate)

这是一个实值的Noiselet变换，压缩感知的图像应用中的的Noiselet观测矩阵 (1) This implementation uses exactly m*log2(m) additions/subtractions. 2) This is a real-valued variation of "dragon" noiselets. 3) This is symmetric and orthogonal. To invert, apply again and divide by m.)