ksvd matlab code
2016-08-23
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function [D,Gamma,err,gerr] = ksvd(params,varargin)
%KSVD K-SVD dictionary training.
% [D,GAMMA] = KSVD(PARAMS) runs the K-SVD dictionary training algorithm on
% the specified set of signals, returning the trained dictionary D and the
% signal representation matrix GAMMA.
%
% KSVD has two modes of operation: sparsity-based and error-based. For
% sparsity-based minimization, the optimization problem is given by
%
% min |X-D*GAMMA|_F^2 s.t. |Gamma_i|_0 <= T
% D,Gamma
%
% where X is the set of training signals, Gamma_i is the i-th column of
% Gamma, and T is the target sparsity. For error-based minimization, the
% optimization problem is given by
%
% min |Gamma|_0 s.t. |X_i - D*Gamma_i|_2 <= EPSILO
%KSVD K-SVD dictionary training.
% [D,GAMMA] = KSVD(PARAMS) runs the K-SVD dictionary training algorithm on
% the specified set of signals, returning the trained dictionary D and the
% signal representation matrix GAMMA.
%
% KSVD has two modes of operation: sparsity-based and error-based. For
% sparsity-based minimization, the optimization problem is given by
%
% min |X-D*GAMMA|_F^2 s.t. |Gamma_i|_0 <= T
% D,Gamma
%
% where X is the set of training signals, Gamma_i is the i-th column of
% Gamma, and T is the target sparsity. For error-based minimization, the
% optimization problem is given by
%
% min |Gamma|_0 s.t. |X_i - D*Gamma_i|_2 <= EPSILO
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