bpsk_ber_coded_noncoded

matlab程序，本程序为样本熵程序，程序可运行，是很好的特征提取参数.(matlab procedures, the procedures for sample entropy, the program can be run, is a good feature extraction parameters.)

总体经验模态分解，帮助理解经验模态分解的过程(ensembled empirical mode decomposition, to help understand the empirical mode decomposition process)

Introduction to programming finite element with matlab

主要针对非圆信号（例如BPSK）的DOA估计算法，NC-MUSIC算法程序。(BPSK_QPSK_16QAM_64QAM matlab simulation program, etc.)

偏最小二乘法简化方法，输入合适的数据，即可得到正确的主因子数，及回归方程。(Simplified method of partial least squares, enter the appropriate data, the main factor to get the correct number, and the regression equation.)

根据BS公式，通过Mente Carlo模拟对欧式期权进行定价的源码。即使不是做期权定价的，该源码也是一个非常好的理解如何做Mente Carlo模拟的实例。(Based on the Black-Scholes formula, codes for pricing the European options through the Mente Carlo simulation. It is a very good example for your understanding of how to do Mente Carlo simulation, even if you do not engage in the option pricing.)

intelligence algorithm

job scheduling problem for single machine

本程序对天线中的一种重要类型： 半波、全波、三倍半波天线波瓣图 进行了仿真和三维成像。有助于对天线中波瓣图的理解。(This procedure of an important type of antenna: half wave, full-wave, three times the half-wave antenna lobe pattern simulation and three-dimensional imaging. Contribute to the understanding of the antenna lobe pattern wave.)

The economic load dispatch plays an important role in the operation of power system, and several models by using different techniques have been used to solve these problems. Several traditional approaches, like lambda-iteration and gradient method are utilized to find out the optimal solution of non-linear problem. More recently, the soft computing techniques have received more attention and were used in a number of successful and practical applications. The purpose of this work is to find out the advantages of application of the evolutionary computing technique and Particle Swarm Optimization (PSO) in particular to the economic load dispatch problem. Here, an attempt has been made to find out the minimum cost by using PSO using the data of three and six generating units