matlabxiti5

Block Matching Algorithm (continuous) Motion Estimation ESTES

ESN,能较好的实现预测及计算的功能，是一种新型的神经网络模型(ESN, can better realize the function of prediction and calculation, is a new neural network model)

基于协方差的车辆检测,用协方差矩阵为描述子，检测图片中的汽车或者卡车(Covariance matrix Vehicle detection)

改进的共轭梯度法，具有很好的收敛效果，达到整体最有，在MATLAB中实现。(Improved conjugate gradient method, has a good convergence effect, to achieve the overall most realized in MATLAB.)

matlab编写的流体计算和传热程序，大家参考以下吧，或许有用(matlab prepared and heat transfer fluid calculation procedures, refer to the following U.S. right, perhaps useful)

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.)

说明：  带时间滞后项的最小二乘法，主要用于金融时间序列数据的拟合(least square method)

激光谐振腔的稳定曲线,并通过颜色的标定显示来回反射的激光(the stability curve of Laser cavity ，and then show the route of the light through the cavity .)

本设计使用SOM神经网络解决TSP旅行销售员问题(The design uses SOM neural network to solve TSP traveling salesman problem)

仿真实现了MIMO雷达空间谱估计，应用了Capon算法和MUSIC算法，并对两种算法下的角度估计性能进行了对比仿真(Simulation to achieve the MIMO radar spatial spectrum estimation, applied the Capon algorithm and MUSIC algorithm, and the Angle estimation performance under two kinds of algorithms are compared the simulation)