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lab4
matlab实现的频率空间转换，含完整实验报告(matlab implementation of the frequency space conversion, including a full lab report)
- 2010-11-12 16:41:49下载
- 积分：1
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fmdemod
将音乐信号fm调制并解调，光看波形和频谱(Fm music signal modulation and demodulation, optical waveform and spectrum look)
- 2008-05-16 22:42:55下载
- 积分：1
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plotmark
When doing black and white figures with several curves, it is sometimes
difficult to uniquely identify each curve, since the number of different line
styles is quite limited.
- 2011-09-09 17:05:03下载
- 积分：1
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ErrorCalc
Error calculation set. For statictic purposes
- 2013-11-19 22:35:26下载
- 积分：1
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Ball_sliding_on_an_inclined_plane_motion
模拟斜面上滑动的小球运动，工程力学课程设计(Ball sliding on an inclined plane motion)
- 2011-01-01 13:30:55下载
- 积分：1
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skindetection
To detect skin color based on threshold. Using simple method , with LOC less than 100 but efficient
- 2011-05-25 02:08:44下载
- 积分：1
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QPSK
QPSK调制与解调，低通滤波器采用了时域和频域两种实现方式，截止频率fc = 200hz,采样频率fs= 1000hz,欢迎下载参考！(QPSK modulation and demodulation, using a low-pass filter with a time domain and frequency domain implemented way, the cutoff frequency fc = 200hz, the sampling frequency fs = 1000hz.Welcome to download !)
- 2013-08-15 10:34:51下载
- 积分：1
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sy3_1
潮流计算，潮流计算，潮流计算，潮流计算，潮流计算，潮流计算，潮流计算，(Power flow calculation)
- 2020-12-01 22:29:27下载
- 积分：1
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Kalman
Kalman滤波的matlab例程,内含kalman滤波方法的介绍.(Kalman filtering matlab routines, including the introduction kalman filtering method.)
- 2009-03-21 10:12:58下载
- 积分：1
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优秀论文及配套源码 SVM Short-term-Load-Forecasting
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 )
- 2021-04-01 17:09:08下载
- 积分：1
