matlab_fft

这是用牛顿法做的，绝对正确无误，请放心下载。(This is done using Newton s method is definitely correct, please rest assured that download.)

说明：  此为LDPC低密度校验码的编译码的原理与应用的详细介绍。包括各种信道模型下的仿真结果，有助于更好的学习通信系统的编译码过程的实现。(This is the LDPC coding and decoding LDPC codes principles and applications in detail. Including channel model simulation results, contribute to a better communication system of learning to achieve encoding and decoding process.)

电力行业通用技术标准 电力系统安全稳定控制技术导则(Power system security and stability control technology guide)

粒子群优化方法，并行计算，收敛速度快，利于全局优化，算法实现简单(Particle Swarm Optimization)

数值积分方法计算积分方程，利用复化辛普森公式离散积分项(Integral equation numerical integration method, the use of complex discrete integral term of Simpson formula)

说明：  支持向量机最初用来解决模式识别问题，目的是发现泛化性能好的决策规则。然而，随着Vapnik的 不敏感损失函数的引入，支持向量机已经扩展为解决非线性回归估计问题，而且与神经网络方法相比，有着显著的优越性，被认为是人工神经网络方法的替代方法，已经成为目前机器学习领域的研究热点和焦点。(Support vector machine (SVM) was originally used to solve the problem of pattern recognition. However, with the introduction of Vapnik's insensitive loss function, support vector machine (SVM) has been extended to solve the problem of nonlinear regression estimation. Compared with neural network method, support vector machine (SVM) has obvious advantages. It is considered as an alternative method of artificial neural network method, and has become the research hotspot and focus in the field of machine learning.)

这是一个关于永磁同步电机矢量控制的simulink模型，可以同过本历程自己修改模块得到自己想要的结果(This is a permanent magnet synchronous motor vector control on the simulink model, you can modify the same over the course of their module get the results you want)

经验模态分解的matlab源程序，手工编写样条插值方法(Empirical mode decomposition matlab source, manual preparation of spline interpolation method)

1基于Matlab的遥感图像融合效果的客观评价方法(1 objective evaluation of the effect of the remote sensing image fusion based on Matlab.)

In many applications, such as biomedical engineering, it is often required to obtain specific periodic source signals. In this paper, we propose a two-stage based approach for extracting periodic signals. At the first stage, the autocorrelation property of the desired source signal is exploited to roughly extract the desired source signal. At the second stage, the extracted signal is further processed as cleanly as possible, based on the higher-order statistics. Simulations on artificially generated data and real-world ECG data have showed its better performance, compared with many existing extraction algorithms.