Adaptive_filtering_toolbox

所属分类:matlab编程
开发工具:matlab
文件大小:60KB
下载次数:94
上传日期:2010-03-04 20:01:46
上 传 者bolt16
说明:  The matlab codes for adaptive filtration and echo-cancelleration, codes using LMS, RLS, DFT, Subband filtration.

文件列表:
Adaptive_filtering_toolbox_v2 (0, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms (0, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Affine_projection.m (4369, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Dual_sign.m (3866, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\LMS.m (3451, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\LMS_Newton.m (4307, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\NLMS.m (3638, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Power2_error.m (3974, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Sign_data.m (3477, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Sign_error.m (3494, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Tdomain.m (5411, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Tdomain_DCT.m (5533, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\Tdomain_DFT.m (5574, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Affine_projection.m (4318, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Dual_sign.m (4121, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_LMS.m (4062, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_LMS_Newton.m (4530, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_NLMS.m (4191, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Power2_error.m (4179, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Sign_data.m (3923, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Sign_error.m (3925, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Tdomain.m (4604, 2009-09-03)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Tdomain_DCT.m (4531, 2009-03-17)
Adaptive_filtering_toolbox_v2\LMS_Based_Algorithms\example_systemID_Tdomain_DFT.m (4531, 2009-03-17)
Adaptive_filtering_toolbox_v2\RLS_Algorithms (0, 2009-09-03)
Adaptive_filtering_toolbox_v2\RLS_Algorithms\RLS.m (5170, 2009-09-03)
Adaptive_filtering_toolbox_v2\RLS_Algorithms\RLS_Alt.m (5237, 2009-09-03)
Adaptive_filtering_toolbox_v2\RLS_Algorithms\example_systemID_RLS.m (4672, 2009-03-23)
Adaptive_filtering_toolbox_v2\RLS_Algorithms\example_systemID_RLS_Alt.m (4750, 2009-03-23)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms (0, 2009-09-03)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\SM_AP.m (5698, 2009-09-03)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\SM_BNLMS.m (4773, 2009-09-03)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\SM_NLMS.m (4293, 2009-09-03)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\Simp_SM_AP.m (5124, 2009-09-03)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\Simp_SM_PUAP.m (6238, 2009-09-03)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\example_systemID_SM_AP.m (4845, 2009-03-26)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\example_systemID_SM_BNLMS.m (4549, 2009-03-26)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\example_systemID_SM_NLMS.m (4603, 2009-03-26)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\example_systemID_Simp_SM_AP.m (4742, 2009-03-26)
Adaptive_filtering_toolbox_v2\Set-membership_Algorithms\example_systemID_Simp_SM_PUAP.m (5018, 2009-03-26)
... ...

In order to facilitate the usage of the Adaptive Filtering Toolbox, the authors have chosen to use a similar prototype for all the functions, whenever it was possible. Following we illustrate such prototype: function [outputVector,... errorVector,... coefficientVector] = Affine_projection(desired,input,S) where, . desired: is the desired signal refered as d(k) in [1] . input: is the input signal refered as x(k) in [1] . outputVector: is the output of the adaptive filtering refered as y(k) in [1] . errorVector: is the error signal refered as e(k) in [1] . coefficientVector: is the impulse response of the adaptive filter refered as w(k) in [1] . S: is a structure in which the user sets specific parameters of the algorithm (in this case, the Affine_projection algorithm). For further details about a specific function, type: "help " Ex: > help Affine_projection If it is the first time using the toolbox, it might be helpful to take a look at the example scripts (which provide a simple system identification scenario) first. [1] P. S. R. Diniz, "Adaptive Filtering: Algorithms and Practical Implementation", 3rd Ed., Springer. Adaptive_filtering_toolbox_v1 ============================= - Provided all the adaptive filtering algorithms presented in chapters 1 to 6 of [1]. Adaptive_filtering_toolbox_v2 (September 3, 2009) ================================================= - Correction to script "example_systemID_Dual_sign.m": (thanks to Professor Marcelo Ventura) It was calling the "Sign_error" function instead of calling the "Dual_sign" one.

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