frequency-hopping

说明：  基于MATLAB车牌识别的应用，请大家多多指教(Application of MATLAB-based license plate recognition, please bear teach)

是一本英文版的关于matlab在金融领域应用的书籍，对于需要分析统计海量数据的人有一定帮助哦(This text describes a set of MATLAB functions that implement a host of econometric estimation methods. )

蚂蚁算法在路由中的应用,提升网络路由选择性能，运行环境matlab。(ant applicationg)

用LAPLACE方法求解多维沃尔泰拉方程，此处为一个变元的方程，由于该方程同时含有微分和积分，一般求解有一定的困难。此处为MATLAB程序，注意不同的初始条件(used method for multiple preoperational Ertaila equation here as a variable element of the equation, As the same time contain differential equations and integral, the general solution is definitely difficult. MATLAB here for the procedure to different initial conditions)

DC-Motor Simulation and System Identification

用于运动仿真 主要用于移动机器人路径规划问题,进行事实仿真,(for major sports simulation for mobile robot path planning, simulation fact,)

PLS - DN是一个有限的牛顿为解决非退化的分段线性系统的算法。 PLS - DN的展品可证明半迭代 财产即在全球范围内的精确解在有限数量的迭代算法收敛。被证明是收敛速度 至少前终止线性。 广泛的算法是在我们的AISTATS 2011纸描述：“一个非退化的分段线性系统的有限牛顿算法”。此演示包重新运行 在解决非负最小二乘法（NNLS）问题上的三个稀疏的设计矩阵，从哈威尔波音收集（达夫等人，1989年）第4.2节的实验。 随着PLS - DN，此演示包建议实施五 其他NNLS求解：LCP_Fisher_Newton，LCP_Lemke，PQN，TRESNEI，和SCD (PLS- DN is a finite non-degenerate Newton to solve the piecewise linear system algorithms. PLS- DN exhibits semi-iterative property to prove that the exact solutions worldwide in a limited number of iterative convergence. Proved to be terminated before the linear convergence rate at least. A wide range of algorithms in our AISTATS 2011 paper describes: " a non-degenerate sub-linear systems with limited Newton algorithm." This demo package to re-run in the settlement of non-negative least squares (NNLS) on the design of the three sparse matrices from the Harwell Boeing collection (Duff et al, 1989) Section 4.2 of the experiment. With PLS- DN, this demonstrates the implementation of five other NNLS package proposed solution: LCP_Fisher_Newton, LCP_Lemke, PQN, TRESNEI, and SCD)

基于延迟线的数字脉冲宽度调制，用于电力电子设备的触发信号产生(puls wide modulator based on delayline)

Latent SVM code voc-release 5

卡尔曼滤波器是一个对动态系统的状态序列进行线性最小误差估计的算法，一般用于线性系统。一般在运动跟踪领域中摄像机相对于目标物体运动有时属于非线性系统，但由于在一般运动跟踪问题中图像采集时间间隔较短，可近似将单位时间内目标在图像中的运动看作匀速运动，采用卡尔曼滤波器可以实现对目标运动参数的估计。(Kalman filter is a state sequence of linear dynamic systems smallest error estimation algorithm for linear systems in general. Usually in the field of motion tracking camera motion with respect to the target object may belong to nonlinear systems, but in general due to motion tracking problems shorter image acquisition time interval, a unit of time can be approximated to the target motion in the image is regarded as uniform motion, Kalman filter can achieve the target motion parameter estimation.)