logical-effort

在功率谱估计中采用Bartlett法对信号进行功率谱估计。(In the power spectrum estimation method used in Bartlett signal power spectrum estimation.)

利用matlab计算探月卫星速度的教程 清晰易懂~(Calculated using matlab tutorial lunar satellite speed lucid ~)

说明：  EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精度。 (EKF only uses non-linear function of the first-order Taylor expansion of some partial derivatives (ignoring higher order terms), often leading to the posterior distribution of the state estimates to generate large errors affect the performance of filtering algorithms, which affect the whole tracking system performance. Recently, the field of adaptive filtering algorithms and the emergence of new- and tasteless transform Kalman filter (Unscented Kalman Filter-UKF). EKF UKF filter is different from the idea that it points through the design of a small amount of σ by σ point spread through the nonlinear function to calculate the random vector first and second order statistical properties of the transmission. Therefore it is better than the EKF filter nonlinear characteristics equation of state approach, which is more than the EKF filter estimation accuracy.)

用于图像识别中，采用matlab编写的程序，lbp算法的实现(For image recognition, using matlab preparation procedures, lbp Algorithm)

useful resources in matlab

多重信号分类算法 很具体 值得学习 毕业设计哦(Multiple signal classification algorithm is very specific graduation Well worth learning)

matlab实现的最小二乘法拟合程序，其中包含了数值结果分析过程。(matlab implementation of least-squares fitting program, which includes the analysis of the numerical results.)

ELECTROMAGNETIC FINITE-DIFFERENCE TIME-DOMAIN VERSION 1.20, RELEASE 1

《空间谱估计理论与算法》中的信源数目估计，Matlab程序源代码(" Space Spectral Estimation Theory and Algorithms" in the estimated number of sources, Matlab source code)

说明：  《面向matlab工具箱的神经网络理论与应用》配套源程序，非常的不错("Matlab Toolbox for the neural network theory and application of" complementary source, very good)