data-analysis-code

说明：   由于使用了大量数目的子载波，这就使得多载波系统对多种同步误差都很敏 感。同步误差可分为两大类:载波相位 (due to the use of the large number of subcarriers, which makes multi-carrier systems for a variety of synchronization errors are very sensitive. Synchronization error can be divided into two categories : carrier phase)

Functions for aligning images by rotation and translation: im_reg_MI.m MI2 - calculating Mutual information joint_h - calculating Joint histogram Mutual information is calculated using joint histogram calculation between two images.

关于魏格纳分布的计算代码，可以得到IMF和各个特征频率以及进行希尔伯特变换。(About calculation code Wigner distribution can be obtained as well as the IMF and the individual characteristics of the frequency of the Hilbert transform.)

说明：  利用遗传算法和粒子群优化算法优化支持向量机(Using genetic algorithm and particle swarm optimization algorithm to optimize support vector machine)

本书介绍了光学设计的理论和并给出了一些实例及相关的参考文献，对于从事镜头设计的研究者来说具有很好的参考价值。(This book introduces the theory and optical design and gives some examples and related references for researchers engaged in the lens design is a good reference value.)

优秀论文及配套源码。首先阐述了负荷预测的应用研究现状，概括了负荷预测的特点及其影响因素，归纳了短期负荷预测的常用方法，并分析了各种方法的优劣；接着介绍了作为支持向量机（SVM）理论基础的统计学习理论和SVM的原理，推导了SVM回归模型；本文采用最小二乘支持向量机（LSSVM）模型，根据浙江台州某地区的历史负荷数据和气象数据，分析影响预测的各种因素，总结了负荷变化的规律性，对历史负荷数据中的“异常数据”进行修正，对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响，而目前依然是基于经验的办法解决。对此，本文采用粒子群优化算法对模型参数进行寻优，以测试集误差作为判决依据，实现模型参数的优化选择，使得预测精度有所提高。实际算例表明，本文的预测方法收敛性好、有较高的预测精度和较快的训练速度。(first expounds the recent application research of load forecasting, summarized the characteristics of load forecasting and influencing factors, summed up common methods of short-term load forecasting, and analyzed the advantages and disadvantages of each method then introduced statistical learning theory and the principle of SVM as the basis of support vector machine (SVM ) theory, SVM regression model is derived this paper adopted least squares support vector machine (LSSVM) model, according to the historical load data and meteorological data of a certain area of Zhejiang Taizhou, Analysised the various factors affecting the forecast, summed up the regularity of load change , amended "outliers" in the historical load data,the load forecasting factors to be considered were normalized. The two parameters of LSSVM have a significant impact on the model, but it is still soluted based on the experience currently. So, this paper adopted particle swarm optimization algorithm to optimized )

BER_QPSK QPSK MODULATION ANALYZE IN BER

基于simulink的Jiles模型参数提取。使用中需使用simulink的parameter estimation功能(Jiles artheron model parameter extraction based on simulink)

电流谐波分析,对电力方面的电流做谐波分析(Current harmonic analysis, the current electricity do harmonic analysis)

说明：  轴承外圈故障仿真的信号，简单实用，欢迎朋友提供内圈，滚动体，保持架仿真信号！(Signal of Bearing Outer Ring Fault Simulation)