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这是一个用matlba实现双声道和单声道的录音器的程序(Dual-channel and single channel recording device)

This routine draws a circle with center defined as X_CENTER,,Y_CENTER, radius as a scaler RADIUS.

HMC5883磁力计使用前必须进行校准，这个matlab程序用来拟合磁力计的数值，然后得出补偿值(HMC5883 magnetometer must be calibrated before use, the procedure used to fit the numerical matlab magnetometer, and then come to the compensation value)

image deionising using various filter in matlab

APF svpwm方式的matla simulink模型(Matla simulink model APF svpwm way)

Direct Power control of Doubly fed induction generator with/without MPPT strategy

实时跟踪摄像头获取视频中的红色部分，算法由Matlab实现。计算机要有摄像头或连接USB摄像头，Matlab通过自身函数提取视频跟踪。 包含两个文件，word说明了matlab提取视频方法。m文件实现算法，其中摄像头参数部分代码可能视具体情况修改。(Get real-time tracking camera video in the red part of the algorithm by Matlab implementation. Computer must have a camera or connect a USB camera, Matlab function to extract the video track by itself. Contains two files, word describes a method to extract video matlab. m file algorithm, which camera parameters of the code, as the case may be modified.)

数字信号处理应用仿真程序，感谢北航自动化学院王秋生老师(Digital signal processing applications simulation program, thanks to Northern College of Automation, WANG Qiu-sheng teacher)

曲线拟合和多项式拟合-2，主要用于工程计算，工程优化。(Curve fitting and polynomial fitting, is mainly used for engineering calculations, engineering optimization.)

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 )