Cuckoo-search-algorithm

给出了通信原理课程的相关实验程序源码，包括DSB、ASK，抽样及其滤波、信噪比分析及眼图。(Communication Theory courses give the experimental procedures related to the source, including DSB, ASK, sampling and filtering, signal to noise ratio analysis and eye diagram.)

夫琅和费衍射的matlab仿真，对此方面做了比较详尽阐述(Fraunhofer diffraction of matlab simulation, which has done more elaborate)

comsol 关于光子晶体光纤的程序 仅供大家参考(comsol on photonic crystal fiber program for your reference)

iris normalization with convertion of cartesian to polar

这是一个基于matlab且运用极大似然估计法对伽马分布进行拟合(This is a matlab-based and the use of maximum likelihood estimation method for gamma distribution fitting)

直接序列扩频通信系统误码率的仿真分析PN码同步方法的比较与仿真(Direct Sequence Spread Spectrum Communication System Simulation and Analysis of BER PN Code Synchronization Methods and Simulation)

pu/4 DQPSK matlab modulation code

Abstract—Demand Response (DR) and Time-of-Use (TOU) pricing refer to programs which offer incentives to customers who curtail their energy use during times of peak demand. In this paper, we propose an integrated solution to predict and re-engineer the electricity demand (e.g., peak load reduction and shift) in a locality at a given day/time. The system presented in this paper expands DR to residential loads by dynamically scheduling and controlling appliances in each dwelling unit. A decision-support system is developed to forecast electricity demand in the home and enable the user to save energy by recommending optimal run time schedules for appliances, given user constraints and TOU pricing the utility company. The schedule is communicated to the smart appliances over a self-organizing home energy network and d by the appliance control interfaces developed in this

说明：  无线传感器网络定位算法MDS-MAP仿真的matlab代码(Wireless sensor network localization algorithm MDS-MAP simulation matlab code)

K-nearest neighbors 搜索 聚类时经常使用的一种方法 国外网站转载( The following utilities are provided: - Nearest neighbor - K-Nearest neighbors - Radius Search They al supports N-dimensions and work on double, it is possible to choose if return the distances. Here is a time comparison with a vectrized m-code: N=1000000 number of reference points Nq=100 number of query points dim=3 dimension of points k=3 number of neighbor tic [idc,dist]=BruteSearchMex(p ,qp , k ,k) MEX toc tic [idc,dist]=knnsearch(qp,p,k) VECTORIZED M-CODE toc p=rand(N,dim) qp=rand(Nq,dim) Output: Elapsed time is 0.962640 seconds. Elapsed time is 18.813100 seconds. )