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A-hybrid-least-squares
- A hybrid least squares support vector machines and GMDH approach for river fl ow forecasting-This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares supp
ridcomfort
- 计算加权加速度,车辆平顺性数据分析，用来得到加权加速度均方根值-Calculation of the weighted acceleration, the ride comfort of the vehicle data analysis, used to get the root-mean-square value of weighted acceleration
fusion-evaluation
- 图像融合中常用的评价指标（非常全面）如：平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等。-Image fusion evaluation (very comprehensive): average gradient, correlation coefficient, entropy, cross entropy, joint entropy, mean square error and mutual i
16QAm
- 采用MATLAB编程，产生一个16QAM基带信号，并进行实数倍插值计算。要求符号率为1 MSymbol/s，采用均方根升余弦滤波成形，滚降系数=0.5。产生{…1，0，1，1，…}的伪随机序列，经过映射、4倍成形滤波、FIR半带滤波、实数倍内插滤波，最后输出4.315倍时域/频域响应。给出信号序列经过各级滤波的时域、频域结果-Using MATLAB programming, resulting in a 16QAM baseband signal, and the real multiples
Kalman_sd
- 卡尔曼滤波器相关的程序，对目标的速度均方根误差等进行了仿真-Kalman filter procedure, the speed of the target such as root mean square error simulation
RRMSSDzipM
- RMSD: Root Mean Square Deviation 是一种在分子模拟及预测中非常常见的评价标准，通过Jacobi变换来的到一个大分子与目标分子的相似程度度。常用来评价一个三维结构的预测结果是是否足够准确.作者主页http://dillgroup.ucsf.edu/~bosco/压缩包里的html里还包含有Python代码 -RMSD: Root Mean Square Deviation is very common in molecular modeling and fore
GetData
- 从磁盘中的txt文件中读取数据，并对数据进行均方根计算，并进行粗大误差剔除-Txt file from the disk to read data, and calculated the root mean square data, and the gross error removed
chengxu
- 求两幅存在一定位移或偏差的RGB图像的均方根误差MSE和峰值信噪比PSNR-Seeking two RGB images there is a certain displacement or deviation of the root mean square error (MSE) and peak signal to noise ratio PSNR
quzao
- 仿照着《小波去噪中软硬阈值的一种改良折衷法》一文写的程序，对比了软、硬以及软硬阈值折衷法的信噪比及均方根误差。仿真出来之后，原信号的信噪比是负的，不知道为什么？均方根误差的值也比较大，不知何解？信噪比和均方根误差是参照《基于matlab的小波去噪仿真》：吴伟，《信息与电子工程》 一文写的-Modeled on the written procedures of the hard and soft threshold wavelet de-noising an improved compromis
quality
- 图像质量评价，峰值信噪比（PSNR），均方根误差（mse）-Image quality evaluation, the peak signal to noise ratio (PSNR), root mean square error (mse)
matlab-for-neural-network
- BPnet.m、GRNNnet、RBFnet分别为BP神经网络、GRNN神经网络、RBF神经网络用于预报模型的代码，其中给出预报的精度指标：合格率、确定性系数、均方根误差-BPnet.m, GRNNnet, RBFnet were BP neural network, GRNN neural network, RBF neural network for forecasting model code, which gives the prediction accuracy indicators:
HGT
- WRF模拟结果气象要素的检验对比，包含均方根误差，偏差和相关系数等-WRF simulation test results comparing meteorological elements, including the root mean square error, deviations and correlation coefficients
mean-functions
- calcules the harmonic,mean square root and geometric mean
Monte-Carlo-
- 利用蒙特卡洛仿真算法检验在不同模型下，滤波平均误差、均方根误差的统计结果，得到随机误差，进行滤波分析。-Monte Carlo simulation algorithm testing under different models, statistical results filtered average error, root mean square error, the random error filtering analysis.
CV2D_JDemo
- 对目标进行2维卡尔曼滤波，绘制出了目标轨迹、x、y轴的滤波方差、位置均方根误差和速度均方根误差。-The Kalman filter 2 target, drawn out of the target track, x, y axis variance filter, the position and velocity root mean square error RMSE.
kf_lsd
- 一种考虑观测噪声和系统噪声的滤波算法，绘制出了目标轨迹和跟踪效果、x、y轴的滤波方差、位置均方根误差和速度均方根误差。-Consider an observation noise and system noise filtering algorithm, to map out the trajectory of the target and tracking results, x, y-axis variance filtering, position and velocity RMSE roo
Stroke-encoding
- 行程编码(RLE）,显示原始图像和经编码解码后的图像,显示压缩比,并计算均方根误差-Stroke encoding (RLE), the original image and the display image after encoding and decoding, the compression ratio of the display, and the root mean square error
mse_snr
- 基于蒙洛特实验，通过不同的信噪比，得到信号比和均方根误差的实验结果。-Based on the Mengluote experiment, through different signal to noise ratio, experimental results are obtained to signal ratio and the root mean square error.
1
- 彩色图像分割，计算两图像的均方根误差并显示误差图像及其直方图；多边形顶点连接-Color image segmentation, calculate the root mean square error and display the image and histogram of the image Polygon vertices connected
three-layers-shot-record
- 实现了三层介质的地震记录，雷克子波，卷积，采用均方根速度计算。-Implementation of the earthquake record in three layer medium, Ricker wavelet, convolution, using the root mean square velocity calculation.