Amouzesh-Matlab

说明：  文主要目的是针对讯号频谱分析仪(Signal spectrum analyzer)做功能测试，以确定讯号频谱分析仪之各种运算功能正确，其中测试共 分为正弦与余弦波检查、反假象滤波器检查(Antialiasing Filter Check)、频率响应函数与相位角检查(FRF & Phase Check)、自身能量密度函 数检查(Power Spectrum Check)、动态范围检查(Dynamic Range Check)等五个项目的快速傅立叶转换检查(Fast Fourier Transform Check)，并 对五个项目之测试原理、测试步骤及测试结果加以说明，提供频谱分析仪功能测试之正确方法，亦可作为自制频谱信号处理单元及频谱分 析程式之验证。(The main purpose of the text is for the signal spectrum analyzer (Signal spectrum analyzer) to do functional testing, to determine the signal spectrum analyzer features a variety of computing the right, which is divided into sine and cosine test wave inspection, anti-false filter inspection (Antialiasing Filter Check), the frequency response function and phase angle of inspection (FRF &amp Phase Check), its energy density function check (Power Spectrum Check), dynamic range checking (Dynamic Range Check) and other five projects FFT check (Fast Fourier Transform Check ), and principles of the five test items, test steps and test results to show that the spectrum analyzer to provide the proper testing method may be used as self-spectrum signal processing unit and the spectral analysis of the verification.)

speed controller system for permanent magnet synchrounus motor by pq theory or filed orinted control

There are two files with the same name (vectgui) in this archive. One is Matlab figure file and the other one is Matlab M-file. Please save them under the same directory which Matlab can access.

一段用于数据分类，分级的费舍尔判别分析算法，MATLAB代码(A Fisher discriminant analysis algorithm for data classification and classification, MATLAB code)

基于matlab的巴特沃斯低通滤波器设计程序(Matlab based on the Butterworth low-pass filter design program)

说明：  基于MATLAB单神经元PID控制源程序(MATLAB-based single neuron PID control source)

非线性扩展卡尔曼滤波算法的matlab程序(Description:This is a tutorial on nonlinear extended Kalman filter (EKF). It uses the standard EKF fomulation to achieve nonlinear state estimation. Inside, it uses the complex step Jacobian to linearize the nonlinear dynamic system. The linearized matrices are then used in the Kalman filter calculation. The complex step differentiation seems improving the EKF performance particularly in accuracy such that the optimization and NN training through the EKF are better than through the UKF )

This is source code concerning with chapter 4 of DIP book

Person Identification Using Ear Biometrics

boost电路matlab仿真，输入为带有波动的直流电压 要求占空比为0.5(boost current road)