parallel_iterative_deconvolution-1.9-bin

matlab 信息处理设计 fir滤波器设计(Information processing design fir filter design)

matlab的使用命令大全，可以在做matlab开发的时候给与很好的帮助(the use of matlab command Daquan, you can do matlab developed a good time to give help)

利用newton法，newton-honor法和Stevensen-newton法，解非线性方程的matlab原程序。(Using newton method, newton-honor method and Stevensen-newton method for solving nonlinear equations matlab original program.)

一个实现对直升机进行飞行控制的程序，包括俯仰控制、滚转控制等。(A realization on the helicopter flight control procedures, including pitch control, roll control.)

基于粒子群算法PSO的水火电系统日前调度的经济运行和环境运行单目标优化(PSO algorithm based on particle swarm optimization of hydro-thermal system before scheduling a single run economic performance and environmental goals)

To estimate the input-output mapping with inputs x ％ and outputs y generated by the following nonlinear, ％ nonstationary state space model: ％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)] ％ + 8cos(1.2t) + process noise ％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3 ％ + time varying measurement noise ％ using a multi-layer perceptron (MLP) and both the EKF and ％ the hybrid importance-samping resampling (SIR) algorithm. (To estimate the input-output mapping with inputs x and outputs y generated by the following nonlinear, nonstationary state space model: x (t+ 1) = 0.5x (t)+ [25x (t )]/[( 1+ x (t)) ^ (2)]+ 8cos (1.2t)+ process noise y (t) = x (t) ^ (2)/20+ 6 squareWave (0.05 (t-1 ))+ 3+ time varying measurement noise using a multi-layer perceptron (MLP) and both the EKF and the hybrid importance-samping resampling (SIR) algorithm.)

文件里包含了扩频系统中的m序列码的产生，产生以后的相关运算(File contains the m-sequence spread spectrum system code generation, is produced in the relevant operations)

Design and Performance Evaluation of Subsynchronous Damping Controller With STATCOM

matlab code for low pass

This a camera calibration toolbox for generic lenses. The toolbox can be used to calibrate conventional, wide-angle and fish-eye lens cameras. The calibration is based on viewing a planar calibration object. The intrinsic and extrinsic camera parameters are estimated from control point correspondences between the calibration plane and calibration images. This toolbox is a result of research that has been carried out in the Laboratory of Computational Engineering at Helsinki University of Technology and in the Machine Vision Group at University of Oulu.