Description: 回波抵消器中常用的几种自适应滤波算法有LMS, NLMS, RLS等算法。对现有主要算法的性能进行了分析,并对优缺点进行评价和比较。为了在收敛速度和运算量之间得到很好的折衷,对NLMS算法改进,得到了 PNLMS-Echo cancellation devices commonly used in adaptive filtering algorithm has several LMS, NLMS, RLS, such as algorithms. The main algorithm of the existing performance analysis, and evaluation and comparison of the advantages and disadvantages. For the convergence between computing speed and a good compromise on the NLMS algorithm improvements have been PNLMS Platform: |
Size: 181248 |
Author:东 |
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Description: matlab 的RLS代码,用于可适应滤波器的回声消除功能-matlab for RLS code can be adapted to filter for echo cancellation functionality Platform: |
Size: 12288 |
Author:lulu |
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Description: 考虑了用LMS和RLS算法实现码分多址(CDMA)系统的盲多用户检测matlab仿真。由此可以加深对这方面知识的理解-Consider the use of LMS and RLS algorithm code division multiple access (CDMA) system, blind multiuser detection matlab simulation. It can deepen the understanding of knowledge in this area Platform: |
Size: 1024 |
Author:王会彦 |
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Description: this matlab code for estimating the static linear system(system function is time variable) with Recursive Least Squre and 2 solutions for better result.
1- using the Covariance Matrix Reseting in a specefic time.
2-using the RLS with Forget Factor
this program is written by matlab 7.0.
Here we want to estimate the below function:
1-u^2+(1+tansig(0.1*(t-375)))*u^3+u^5+3*u^7
finally,there are plots for showing results.
-this is matlab code for estimating the static linear system(system function is time variable) with Recursive Least Squre and 2 solutions for better result.
1- using the Covariance Matrix Reseting in a specefic time.
2-using the RLS with Forget Factor
this program is written by matlab 7.0.
Here we want to estimate the below function:
1-u^2+(1+tansig(0.1*(t-375)))*u^3+u^5+3*u^7
finally,there are plots for showing results.
Platform: |
Size: 2048 |
Author:maysam |
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Description: this matlab code for estimating the static linear system(system function is time variable) with Kalman Filter.
this program is written by matlab 7.0.
Here we want to estimate the below function:
this is matlab code for estimating the static linear system(system function is time variable) with Recursive Least Squre and 2 solutions for better result.
1- using the Covariance Matrix Reseting in a specefic time.
2-using the RLS with Forget Factor
this program is written by matlab 7.0.
Here we want to estimate the below function:
1-u^2+(1+tansig(0.1*(t-375)))*u^3+u^5+3*u^7
finally,there are plots for showing results.-this is matlab code for estimating the static linear system(system function is time variable) with Kalman Filter.
this program is written by matlab 7.0.
Here we want to estimate the below function:
this is matlab code for estimating the static linear system(system function is time variable) with Recursive Least Squre and 2 solutions for better result.
1- using the Covariance Matrix Reseting in a specefic time.
2-using the RLS with Forget Factor
this program is written by matlab 7.0.
Here we want to estimate the below function:
1-u^2+(1+tansig(0.1*(t-375)))*u^3+u^5+3*u^7
finally,there are plots for showing results.
Platform: |
Size: 1024 |
Author:maysam |
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Description: In This Matlab Code we Use RLS Method To identify Any System Transfer Function, RLS is based of Recursive Least Squre Algorithm is very important method in System Identification.,In This Matlab Code we Use RLS Method To identify Any System Transfer Function, RLS is based of Recursive Least Squre Algorithm is very important method in System Identification. Platform: |
Size: 2048 |
Author:Hamidreza |
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Description: 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 . Platform: |
Size: 2048 |
Author:metal |
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Description: This computer exercise deals with the RLS algorithm. The example ... Create a function in Matlab that takes an input vector u and a reference .... Program Code. Platform: |
Size: 6144 |
Author:hedi |
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