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3Matlab
- 程序代码说明 P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波
GengerateCrossCorreslation
- 广义互相关算法和最小均方自适应滤波法主要用于两路接收信号的时间延迟估计，进而利用几何方法对目标定位，常用于通信，雷达当中-broad cross-correlation algorithm and the minimum mean square adaptive filter for the two main roads to receive signals in the time-delay estimation, then use geometric method of orientatio
LMS
- 采用一种快速收敛变步长LMS（Least mean square ） 自适应最小均方算法matlab源程序，其中算法所做的工作是用FIR 滤波器的预测系统，对IIR系统进行预测，如果阶数越高越能逼近被预测系统。-Using a fast convergence of variable step size LMS (Least mean square) adaptive least mean square algorithm matlab source, one of algorithm is t
echo1
- Adaptive Echo Canceller Using a Modified LMS Algorithm Abstract –– In this paper, an echo canceller is presented, using an adaptive filter with a modified LMS (Least Mean Square) algorithm, where this modification is achieved coding error on con
wiener
- 维纳滤波 相关程序 基于最小均方误差(MMSE)估计的因果维纳滤波的实现-Wiener filtering procedures based on the minimum mean square error (MMSE) estimate of the causal Wiener filter implementation
test
- 基于最小均方差准则的多带滤波器设计 中心频率分别为4M和9M-Multi-band filter based on minimum mean square error criteria
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
karam
- This program is used for simulation signal mean square error of the Kalman filter
RLS_LMS-code
- RLS_LMS code the Least Mean Squares (LMS) and the Recursive Least. Squares (RLS) algorithms realize the design and simulation of adaptive algorithms in noise canceling, and ... of two algorithms .The adaptive filter with MATLAB are simulated and the
ADAPTIVE-FILTER-MATLAB-CODES
- It has adaptive fiter algorithms such as Least mean Square algorithm and Recursive least mean square algorithm matlab codes.
2.9零均值高斯白噪声通过低通带通滤波器前后特性
- 用matlab仿真零均值高斯白噪声通过低通带通滤波器前后特性，程序完善，结果与理论值非常接近(The zero mean white Gauss noise is simulated by MATLAB, and the program is perfect through the low pass bandpass filter. The result is very close to the theoretical value.)