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10DigitalFilter
- 10种软件滤波方法的示例程序 1、限副滤波 2、中位值滤波法 3、算术平均滤波法 4、递推平均滤波法（又称滑动平均滤波法） 5、中位值平均滤波法（又称防脉冲干扰平均滤波法） 6、限幅平均滤波法 7、一阶滞后滤波法 8、加权递推平均滤波法 9、消抖滤波法 10、限幅消抖滤波法-Software filter of 10 sample program 1, limit the Deputy filter 2, the median filtering meth
pilotbasedchannelestimatininOFDMsystems
- 频域不同导频密度的信道估计在被研究，并且在高低时延信道其信道估计被固定了导频分配时域。频域信道估计是基于插补，多项式的广义线性模型（或最小二乘法）和维纳滤波（或线性最小均方误差法）的方法。时域的信道估计是用线性插补完成的。我们通过测量在基于克拉克散射模型的瑞利衰落信道上并带有QPSK调制的粗误码率，已经比较了所有这些方案的结果。-Different pilot density in frequency domain channel estimate to research, and its hi
xitong
- 对图像进行阈值，对比度，灰度，尺寸的调整，任意角度旋转，锐化，各种滤波处理，包括中值，均值，N*N最值滤波，修复，背景清除，K均值分色，二值化，各种边缘检测，以及后续处理细化等功能。-Threshold the image, contrast, gray, size adjustment, arbitrary angle rotation, sharpening, all kinds of filtering, including the median, mean, N* N the best
LMSAFFilter
- 在分析最小均方自适应滤波器(LMSAF)均方误差(MSE)的收敛性时，文献常用统计自相关矩阵代替瞬时自相关矩阵以简化分析，由此得出的收敛条件比较粗糙。本程序指出：不相关高斯输入情况下，无需如上简化，可依据高斯阶矩因式分解定理得到确切的MSE收敛条件，相应的失调表式能更准确地预报失调-In the analysis of LMS adaptive filter (LMSAF) the mean square error (MSE) convergence, the literature commo
suanfa
- 在许多的数据采集系统中，现场的强电设备较多，不可避免 地会产生尖脉冲干扰,这种干扰一般持续时间短，峰值大，对这样 的数据进行数字滤波处理时，仅仅采用算术平均或移动平均滤波 时，尽管对脉冲干扰进行了1/n的处理，但，其剩余值仍然较大。 这种场合最好的策略是：将被认为是受干扰的信号数据去掉，这 就是防脉冲干扰平均值滤波法的原理。-In many of the data acquisition system, the scene of strong electrical
Multi-targetTracking
- 一篇关于多目标跟踪的文章，结合了Meanshift和粒子滤波两种常用的方法-A Multi-target Tracking Method Based on Mean-shift and Particle Filter
zishiiying
- 自适应滤波算法是自适应滤波器实现过程中较为重要的环节,数字信号处理器的出现为数字信号处理算法的 实现和大规模数据的实时处理提供了可能。通过对自适应最小均方算法(LMS) 及其各种改进算法的Matlab 仿真,进行分 析及归纳比较,得出结论,并在此基础上,提出算法的优化方案,以DSP 为平台,用汇编语言对自适应算法进行了描述,最终 以DSP 为平台完成了自适应滤波器的设计。-Adaptive filtering algorithm is an adaptive filter proce
kalmen1
- 基于卡曼滤波与均值偏移算法的目标跟踪 这是一篇比较好的论文-Based on the Kaman filter and mean shift tracking algorithm is a good paper
lms
- 这是一个自编的最小均方误差的自适应滤波器的程序-This is a self of the minimum mean square error of the adaptive filter procedures
Neural_network_based_on_BP_variable_selection--neu
- 结合BP神经网络应用平均影响值（MIV，Mean Impact Value）方法来说明如何使用神经网络来筛选变量，找到对结果有较大影响的输入项，继而实现使用神经网络进行变量筛选。-BP neural network application with the average impact value (MIV, Mean Impact Value) method to illustrate how to use the neural network to filter the variables
PerformanceAnalysisoftheDeficientLengthLMSAdaptiv
- In almost all analyzes of the least mean-square (LMS) finite impulse response (FIR) adaptive algorithm, it is assumed that the length of the adaptive filter is equal to that of the unknown system impulse response. However, in many practical sit
equality_constraints_of_uncertain_systems_filterin
- 研究了一类离散不确定系统中存在等式约束时的最优滤波问题，在均方误差最小的意义下利用卡尔曼滤波给出了最优解。与传统的不确定滤波结果相比，从理论证明了利用更多信息的约束滤波的估计误差协方差的迹更小。-A class of discrete uncertain systems exist in the optimal filter when the equality constraint problem, the minimum mean square error in the sense of Ka
a
- 基于多目标的跟踪和实现，里面介绍了跟踪算法的现状，以及如何基于mean shift和卡尔曼滤波改进跟踪算法-Based on multi-target tracking and realization, which describes the status of the tracking algorithm, and how mean shift and Kalman filter based tracking algorithm to improve
LinPF
- This a VHDL module that implements linear prediction filter based on NLMS (normalized least mean square). The module takes complex signal as input and output comlex signal (real and imaginary). Tap size is 4, bit precision is set to 12 bits.-This i
wiena
- 分析了维纳滤波器均方误差及滤波性能与阶数和噪声方差之间的关系-Analysis of the Wiener filter and the filter mean square error performance and the order and the relationship between noise variance
ukf
- An implementation of Unscented Kalman Filter for nonlinear state estimation.-Nonlinear state estimation is a challenge problem. The well-known Kalman Filter is only suitable for linear systems. The Extended Kalman Filter (EKF) has become a standarded
Kalman_Filter
- 卡尔曼滤波的源程序，卡尔曼滤波是以最小均方误差为估计的最佳准则，来寻求一套递推估计的算法。-Kalman filtering of source code, Kalman filter based on minimum mean square error for estimating the best criteria to search for a recursive estimation algorithm.
Fast_Kalman_Filter
- 快速卡尔曼滤波的源程序，卡尔曼滤波是以最小均方误差为估计的最佳准则，来寻求一套递推估计的算法。-Fast Kalman filtering of source code, Kalman filter based on minimum mean square error for estimating the best criteria to search for a recursive estimation algorithm.
LMS-RLSAdaptiveFilter
- 数字信号处理，LMS和RLS实例：给定正弦信号s(n)，现在我们获得得是受影响的数据x(n)=s(n)+v(n) ， v(n)为方差1.25的告示白噪声信号，请设计一个滤波器，使其输出与s(n)的均方误差最小，并给出用LMS和RLS算法的自适应求解方法的MATLAB仿真。-Digital signal processing, LMS and RLS instance: Given a sinusoidal signal s (n), now we get the data have affect
SRKB
- the code contains adaptive filter using lms algorithm with zero mean and variance and it minimize the error and equals the output