jade

ECG is the graphical recording of the electrical activity of the heart and recognized biological signal used for clinical diagnosis. The ECG signal is very sensitive in nature, and even if small noise mixed with original signal the various characteristics of the signal changes. The signal voltage level is as low as 0.5 to 5mV and is susceptible to artifacts that are larger than it. The frequency components of a human s ECG signal

这是一个二阶微分方程的分岔图程序，可以画出微分方程状态变量随参数的变化所产生的分岔图。(this is a two-order differential equation bifurcation diagram programme)

基于LMS自适应时延估计算法,可以进行时间延迟的估计。(Delay estimation algorithm based on LMS adaptive research based on the fractional lower order time delay estimation algorithm, including: covariation-based time delay estimation, based on the fractional lower order covariance delay estimation method, as well as the minimum norm when the average P delay estimation method.)

该代码为用matlab编写的训练神经网络拟合典型函数曲线的经典程序。(The code is made for training neural network to fit the classical function profile.)

生成多点地震动，多点激励，地震动的空间变异性。(spatial variation of earthquake ground motion，non-uniform excitation。)

电子信息工程专业课程设计报告，用matlab实现m序列发生器(Electronic and Information Engineering curriculum design, implementation using matlab m-sequence generator)

expectation maximization

非线性系统的模糊逻辑控制（FLC）matlab仿真(Nonlinear systems fuzzy logic control (FLC))

入门级代码，matlab源代码的第一部分(Entry-level code, matlab source code for the first part of the)

本文件对PID参数kp,ki,kd进行寻优，以ITAE作为指标函数。 PSO 文件中有详细的参数设置和寻优过程 GA寻优与PSO寻优作为对比出现 figure1展示了随着迭代次数的变化，适应度函数的收敛情况 figure2展示了kp,ki,kd的迭代情况 ht 文件是用来画图的 问题解决思路.pdf 简要介绍了粒子群算法寻优的过程(In this document, the PID parameters KP, Ki, KD are optimized, and ITAE is used as the index function. PSO file has detailed parameter settings and optimization process GA optimization and PSO optimization as a contrast appear Figure1 shows the convergence of fitness function as the number of iterations changes Figure2 shows the iterations of KP, Ki, and KD The HT file is used for drawing The problem solving idea.Pdf briefly introduces the process of particle swarm optimization)