anbari-ed

mfile for slp simulation without using matlab codes

说明：  一本很好的matlab教程，适合初学者，大家可以慢慢的学习哦 (matlab)

说明：  光伏发电系统，电流电压输出曲线波形吐血土建(Photovoltaic systems, current and voltage waveform output curve vomiting civil)

Introduction to Matlab

Hamilton-Jacobi solver on unstructured triangular grids

包含了阵列信号处理的常见算法，合成孔径雷达（SAR)目标成像仿真，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法。( Contains a common array signal processing algorithm, Synthetic Aperture Radar (SAR) imaging simulation target, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm.)

根据有无固定基础设施，无线局域网又可分为BSS (Basic Service Set)和IBSS (Independent Basic Service Set)。我们要研究的ad hoc网络属于后者。假设在一个ad hoc网络中，移动节点的发射功率PTx总是恒定的。要发送数据的移动节点总是先监听信道，测量接收到的信号功率X，其中X= I + N, I为接收到的干扰，N是噪声。移动节点只有在X＜INThre时，才可以发射。式中，INThre为背景噪声门限。 在仿真中，我们规定每个移动节点的发射功率是常数，PTx = 1W；接收节点接收机的灵敏度Smin = -80 dBm；信号质量 min = 2 dB；系统的背景噪声门限INThre = 1.2e-10。 (According to the availability of fixed infrastructure, wireless local area network can be divided into BSS (Basic Service Set) and IBSS (Independent Basic Service Set). We have to study the ad hoc network belong to the latter. Assuming in an ad hoc network, mobile node s transmission power is always constant PTX. To send data to the mobile node always monitor channel, measuring the received signal power X, which X = I+ N, I was received interference, N is the noise. Mobile node only when X <INThre when it is fired. Where, INThre threshold for background noise. In the simulation, we require that each mobile node s transmission power is constant, PTx = 1W receiver node receiver sensitivity Smin =-80 dBm signal quality )

标准椭圆按中心点频移旋转矩阵得到一般椭圆的方程的方法(Standard ellipse at the center frequency shift rotation matrix of the general method of elliptic equations)

This paper proposes a novel and computationally efficient global I< optimization method based on swarm ntelligence for locating ti nodes in a WSN environment. The mean squared range error of a all neighbouring anchor nodes is taken as the objective function d for this non linear optimization problem. The Particle Swarm c Optimization (PSO) is a high performance stochastic global b optimization tool that ensures the minimization of the objective a function,

DEBLOCKING ieee PAPERS