gaosi

说明：  实验3 离散系统的差分方程 能够帮助实现信号与系统作业习题和相关方程解法(Experiment 3, differential equations discrete signals and systems can help achieve operational exercises and related equations for)

Multicore - Parallel Processing on Multiple Cores (Multicore- Parallel Processing on Multiple Cores )

灰色预测gm（1-1）算法，用于短期时间序列预测，包含残差检验等各种必要检验(Gray predicted all the necessary inspection gm (1-1) algorithm for short-term time series prediction, including residuals inspection)

说明：  GDOP(Geometric Dilution of Precision) 几何精度因子是衡量一个定位系统精度的重要标准之一。 运行程序sGDOP.m可得到三站GDOP仿真结果，更改程序中s_x,y,z可以更改阵列的几何排列。运行程序fGDOP.m得到四站GDOP仿真结果。(GDOP (geometric division of precision) geometric accuracy factor is one of the important standards to measure the accuracy of a positioning system. Running the program sgdop. m, we can get the simulation results of three stations GDOP, and changing the geometry of the array by changing the program s _ x, y,z. Running the program fgdop.m, the simulation results of four stations GDOP are obtained.)

耳蜗实质上相当于一个滤波器组，耳蜗的滤波作用是在对数频率尺度上进行的，在1000HZ下，人耳的感知能力与频率成线性关系；而在1000HZ以上，人耳的感知能力与频率不构成线性关系，而更偏向于对数关系，这就使得人耳对低频信号比高频信号更敏感。Mel频率的提出是为了方便人耳对不同频率语音的感知特性的研究。频率与Mel频率的转换公式为(Cochlear substantially equivalent to a filter set, cochlear filter is used on logarithm frequency scale, under the 1000 hz, the perception of the human ear and a linear relationship with frequency In more than 1000 hz, the perception of the human ear does not constitute a linear relationship with frequency, and prefer to logarithmic relationship, which makes the human ear is sensitive to low frequency signal is better than high frequency signal. Mel frequency is put forward in order to facilitate the ear of the study of speech perception characteristics of different frequency. For frequency and Mel frequency conversion formula )

相位解缠是INSAR数据处理的重要步骤，本文用基于FFT的最小二乘法实现实现相位解缠(Phase unwrapping)

室内无线定位技术，基于RSA算法的matlab仿真程序(Indoor wireless positioning technology, based on the RSA algorithm matlab simulation program)

基于bregman算法在一维、二维、三维信号处理中的应用matlab工具箱(This toolbox provides the source code associated with the Bregman Cookbook Doc: - BregmanCookbook.pdf In 1D: -L1_SplitBregmanIteration.m : performs the recovery of a sparse signal affected by a known linear operator In 2D: -AddCurveletArray.m : sum the curvelet coefficients of two decomposition structures -AddFrameletArray.m : sum the framelet coefficients of two decomposition structures -ATV_NB_Deconvolution.m : performs the Nonblind Anisotropic Total Variation Deconvolution -ATV_ROF.m : performs the Anisotropic Total Variation Denoising -ITV_ROF.m : performs the Isotropic Total Variation Denoising -Curvelet_NB_Deconvolution.m : performs the Nonblind Deconvolution based on Curvelet sparsity -Framelet_NB_Deconvolution.m : performs the Nonblind Deconvolution based on Framelet sparsity (Analysis approach) -Framelet_NB_Deconvolution2.m : performs the Nonblind Deconvolution based on Framelet sparsity (Synthesis approach) -ShrinkCurvelet.m : performs the shrinkage of cu)

this is an method for mode estimation with random decerment technique for ambient techniqe with wavevelet method

可以计算当发射端未知CSI时，MIMO信道在不同SNR下的遍历容量(ergodic capacity)