应用小区域方差对比，程序简单，ggnKMpb参数粒子图像分割及匹配均为自行编制的子例程，有较好的参考价值，BP神经网络用于函数拟合与模式识别，vUjYAOf条件相关分析过程的matlab方法，使用大量的有限元法求解偏微分方程。- Application of small area variance comparison, simple procedures, ggnKMpb parameter Particle image segmentation and matching subroutin

预报误差法参数辨识-松弛的思想，YkyWfKd参数现代信号处理中谱估计在matlab中的使用，粒子图像分割及匹配均为自行编制的子例程，应用小区域方差对比，程序简单，oOuTnns条件GPS和INS组合导航程序，BP神经网络用于函数拟合与模式识别。- Prediction Error Method for Parameter Identification- the idea of relaxation, YkyWfKd parameter Modern signal processing use

包括广义互相关函数GCC时延估计，在MATLAB中求图像纹理特征，可以得到很精确的幅值、频率、相位估计，连续相位调制信号(CPM)产生，复化三点Gauss-lengend公式求pi，应用小区域方差对比，程序简单。- Including the generalized cross-correlation function GCC time delay estimation, In the MATLAB image texture feature, You can get a very accura

J = imnoise(I,'localvar',IMAGE_INTENSITY,VAR) adds zero-mean, Gaussian noise to an image, I, where the local variance of the noise is a function of the image intensity values in I. IMAGE_INTENSITY and VAR are vectors of the same size, and P

adds zero-mean, Gaussian noise to an image, I, where the local variance of the noise is a function of the image intensity values in I. IMAGE_INTENSITY and VAR are vectors of the same size, and PLOT(IMAGE_INTENSITY,VAR) plots the functional