LD_demo

v(k)随机信号，输入信号为幅值为M序列程序.利用极大似然递推进行参数辨识，文件的*m文件，可以直接运行，能直接辨识出参数，绘制误差曲线等，程序中带有详细注释。(v (k) random signal, the input signal amplitude for the M series for the process. the use of recursive maximum likelihood parameter identification, documentation* m files, you can directly run directly identified parameters, such as mapping error curve, procedures with detailed notes in.)

介绍小波的基本概念,并对图像进行压缩,消噪,增强,融合以及平滑处理.(introduced the basic concepts, as well as image compression, denoising, enhancement, integration and smooth handling.)

简单的emd开发程序，matlab程序，含试验数据。(EMD developed a simple procedure, matlab program, including test data.)

根据gabor滤波器的定义，用matlab创造gabor滤波器(According to the definition of gabor filter used to create gabor filter matlab)

有限单元法求解一阶偏微分方程，使用的方法是加权余量法，比二阶方程更加可靠(Finite element method for second order partial differential equations, a method using a weighted residual method is more reliable than the first-order equation)

PMAC的一个很全的较好的培训资料 ，包括较全的pamc产品介绍(pmac training)

机动目标一阶加速度的频率普分析，以及多普勒展宽，相干积累。以70km，径向速度700m，加速度20m/s^2目标为例(An acceleration of maneuvering target frequency bands Pu analysis, and Doppler broadening, coherent accumulation. To 70km, the radial velocity 700m, acceleration 20m/s ^ 2 goals, for example)

基于卡尔曼滤波和粒子滤波的简单比较，用于高机动目标时时定位，以减少精度损失来换取目标跟踪定位时时性。(Relatively simple Kalman filter and particle filter-based positioning for high maneuvering targets time to time, in order to reduce the loss of precision target tracking in exchange for sex time to time.)

LSVMK Langrangian Support Vector Machine algorithm LSVMK solves a support vector machine problem using an iterative algorithm inspired by an augmented Lagrangian formulation.

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