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Search - lms algorithm - List
[
Industry research
]
Onenewauto-adaptedalgorithm
DL : 0
算法存LMS算法的基础上做了一定的修改,通过在于扰来向设置零点来达到抑制干扰-Algorithm deposit based on the LMS algorithm to do a certain amount of modifications, through the disturbance is set to zero to achieve interference suppression
Date
: 2026-01-01
Size
: 205kb
User
:
李宁
[
Industry research
]
OneimprovementchangeslengthofstrideLMS
DL : 0
在对一些变步长LMS算法分析的基础上,提出了步长因子 (n)与误差信号e(n)之间一种新的非线性函数关系-In a number of variable step size LMS algorithm based on the analysis, put forward a step length factor (n) and error signal e (n) between the non-linear function of a new relationship
Date
: 2026-01-01
Size
: 140kb
User
:
李宁
[
Industry research
]
Severalauto-adaptedalgorithms
DL : 0
本文对LMS、NLMS 以及NVSS 算法的性能进行了比较, 通过仿真发现NLMS 算法的运算速度虽略慢于LMS 算法-In this paper, LMS, NLMS algorithm, as well as the performance of NVSS comparison of NLMS algorithm through the simulation found that the computation speed is slightly slower than the LMS algorithm
Date
: 2026-01-01
Size
: 236kb
User
:
李宁
[
Industry research
]
LMS-algorithm
DL : 0
explain the development of wireless communications
Date
: 2026-01-01
Size
: 322kb
User
:
kumar
[
Industry research
]
adaptive-lms
DL : 0
有源自适应噪声的最常用算法,该算法是基于滤波器的输出信号与期望响应之间的误差的均方值为最小。-Active adaptive noise most commonly used algorithm, which is based on the error between the filter output signal and the desired response minimum mean-square value.
Date
: 2026-01-01
Size
: 1kb
User
:
姜鸿羽
[
Industry research
]
LMS-and-RLS-algorithm--(CDMA)
DL : 0
LMS and RLM code in matlab simulate in MUD CDMA system.
Date
: 2026-01-01
Size
: 3kb
User
:
kiit2013
[
Industry research
]
_L0-Norm-Constraint-LMS-Algorithm
DL : 0
用于稀疏系统辨识的L0范约束的最小均方算法原理研究-For sparse system identification of L0 norm constraint of the least mean square algorithm principle is studied
Date
: 2026-01-01
Size
: 115kb
User
:
yinziyu
[
Industry research
]
Regularized-LMS
DL : 0
归一化的最小均方算法原理及误差分析,LMS入门-Normalized least mean square algorithm principle and error analysis, introduction to LMS
Date
: 2026-01-01
Size
: 726kb
User
:
yinziyu
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