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1114763
- matlab例子自适应滤波最陡下降法特征值扩散度仿真，变步长仿真-Matlab example of adaptive filtering steepest descent method for eigenvalue proliferation simulation, variable step simulation
steepest
- 利用最陡下降法仿真实现了自适应滤波均衡器,该方法用硬件能方便实现.-use of the steepest descent method Simulation of the adaptive filter equalizers, the method can be used to facilitate the achievement of hardware.
lms
- 自适应滤波器,LMS最陡下降法的matlab原代码,需要的可以下
SteepestDescentMethod
- 把最陡下降法编成了程序，输入系数就可以得到最陡下降的点
LMS2
- 数字信号处理的自适应算法，最陡下降法与LMS法比较，画出两者收敛曲线
MATLAB_LMS1
- 自适应滤波器LMS算法的误差性能曲面和等高线，并在等高线上绘出最陡下降法和LMS迭代的轨迹曲线，配合数字信号处理2课程的学习
fig811
- 自适应滤波器的最陡下降法示意图-adaptive filter steep decline in the most schematic
mydspexp1_bsdu
- 用matlab写的维纳滤波，最陡下降法的实现例程。-Matlab written by Wiener filtering, the steepest descent method to achieve routine.
lms_flp32
- 最陡下降法的梯度估计matlab小程序，对初学者有借鉴意义-Steepest gradient descent method is estimated matlab small procedures, there is reference for beginners
lms_code
- lms源码这是实验的代码 为了对理论进行实际的理解 仅作参考 1． 随机逼近算法模块 2． 抗噪检验模块 3．最陡下降法模块-This is the experimental lms source code to the actual understanding of the theory of reference only 1. Stochastic approximation algorithm for module 2. Anti-noise test module 3
Nonlinear_Programming
- 非线性规划中的最陡下降法、BFGS方法和共轭梯度法matlab源程序（3－拟牛顿BFGS方法）.m-Non-linear programming in the steepest descent method, BFGS and conjugate gradient method matlab source code (3- Quasi-Newton BFGS method). M
Equalizer_LSM
- 基于LM算法实现的均衡器。采用梯度估计近似实现最陡下降法。给出最后实验误差平方的均值曲线图。有完整的注释。-LM algorithm based on the equalizer. Similar to the realization of the estimated gradient steepest descent method. Finally, given the experimental error of the mean-square curve. Note complete.
cc
- 实现最陡下降法,研究步长因子和特征扩散度对收敛速度的影响-Achieve the steepest descent method to study the characteristics of step length factor and the proliferation of degree of influence on the convergence rate
rootmusic-ld
- 数字信号处理中的 LD算法 最陡下降法，root music 算法 这是一个源程序，提高参考-LD digital signal processing algorithms in the steepest descent method, which is a source to enhance information
self_adaptive_filter
- 自适应滤波器，包括LMS算法和最陡下降法，以及对LMS算法的一些对比-Adaptive filters, LMS algorithm and steepest descent method, and comparison of some of the LMS algorithm
puxianzengqiang
- 利用最陡下降法分离宽带和窄带信号，实现谱线增强-you can separate broadband and narrowband signal by the steepest descent method to achieve line enhancement
1
- 基于lms算法的干扰自适应抵消LMS算法是基于最陡下降法的统计估计的最小均方值算法，令误差的均方值达到最小时的抽头系数的值即为最优解。LMS算法抽头系数w的变化方向为代价方程的负梯度方向。-Lms algorithm based on adaptive interference cancellation algorithm is the LMS steepest descent method based on statistical estimation of the least mean sq
puxianzengqiang
- 谱线增强器的代码，里面包含最陡下降法的实现，是华中科技大学出版的现代数字信号处理课后题3.16的答案，对理解谱线增强器和最陡下降法的实现有很大帮助。-Line enhancer code, which contains the implementation of the steepest descent method, is published by the Huazhong University of Science after-school modern digital signal pro
zishiying
- MATLAB最陡下降法自适应滤波器的数据，以及处理程序·-MATLAB method of steepest descent adaptive filter data, and processing
sparse_wsf
- 使用加权子空间拟合（WSF）实现稀疏均匀圆阵DOA估计。优化过程用的是最陡下降法。-Using weighted subspace fitting (WSF) SPARSE DOA estimation with uniform circular arrays. Optimization process using a steepest descent method.