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LSH 和e2LSH算法，感觉hash函数不怎么好。(LSH and e2LSH algorithm, hash function is not very good feeling.)

用局部参数最优化方法设计一个模型参考自适应系统,可调增益的初值Kc(0)=0.2，给定值r(t)为单位阶跃信号，即r(t)=A×1(t)。 要求： 1把连续系统离散化(采样时间可取0.1)。 2编制并运行这个系统的计算机程序(注意调整B值，使系统获得较好的自适应特性)。 3记录ym、yp的曲线 记录kp×kc的曲线 记录广义输出误差e的变化曲线。 4在参数收敛后，让Kp=2变为Kp=1，重新观察Kp×Kc及e的变化曲线。 5找出在确定的B值下，使系统不稳定的A值(阶跃信号的幅值)，并与用劳斯稳定判据计算的结果比较。 (With local parameter optimization method to design a model reference adaptive system, adjustable gain initial Kc (0) = 0.2, for a given value of r (t) for the unit step signal that r (t) = A × 1 ( t). Requirements: a continuous system discretization (sampling time of 0.1 preferred). 2 compiled and run the system computer program (Note B to adjust the value of the system to obtain better adaptive characteristics). 3 records ym, yp curve record kp × kc curve records generalized output error e curves. 4 parameter convergence, let Kp = 2 into the Kp = 1, re-observed Kp × Kc and e curves. B-5 to find value in determining the next, making the system unstable A value (step signal of amplitude), and using Routh stability criterion and the comparison of the results calculated.)

信号的相关性是信号本身很重要的性质，本程序就是求随机信号的自相关性。(Signal is the relevance of the signal itself is very important properties, this procedure is for the random signals between autocorrelation. )

汽车七自由度动力学系统，能完成汽车平顺性的仿真。(The seven degree of freedom dynamic system of vehicle can complete the simulation of vehicle ride comfort)

一个简单的多个agent通过编队控制形成一个编队队形。(multi-agent formation)

基于严格博弈论的干扰对齐算法，将博弈论与干扰对齐相结合。(Based strictly on game theory interference alignment algorithm, Game Theory and interference alignment combined.)

tdoa定位算（nlos情况）法用于无线传感器网络定位问题，可以求解定位算法的坐标值(talor algorithm for the localization problem in wireless sensor networks, localization algorithm can solve the coordinate value)

拉格朗日内插法的matlab实现 改进后可用于多种用途(Matlab Lagrange interpolation method can be used to achieve the improved multi-purpose)

k-nn algorithm for classify

generates a spatial environment with a variable number of uniformly distributed base stations and randomly placed user