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d-kitamura committed Dec 1, 2019
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58 changes: 28 additions & 30 deletions ILRMA.m
View file
@@ -1,34 +1,32 @@
function [Y, cost, W] = ILRMA(X, type, It, nb, drawConv, normalize, W, T, V, Z)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Independent low-rank matrix analysis (ILRMA) %
% %
% Coded by D. Kitamura (d-kitamura@ieee.org) on 1 Apr, 2018 (ver1.0). %
% %
% Copyright 2018 Daichi Kitamura %
% %
% These programs are distributed only for academic research at %
% universities and research institutions. %
% It is not allowed to use or modify these programs for commercial or %
% industrial purpose without our permission. %
% When you use or modify these programs and write research articles, %
% cite the following references: %
% %
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper) %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation unifying independent vector analysis and %
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24, %
% no. 9, pp. 1626-1641, September 2016. %
% %
% # Book chapter (The algorithm was renamed as "ILRMA") %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation with independent low-rank matrix analysis," %
% Audio Source Separation. Signals and Communication Technology., %
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018. %
% %
% See also: %
% http://d-kitamura.net %
% http://d-kitamura.net/en/demo_rank1_en.htm %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Independent low-rank matrix analysis (ILRMA)
%
% Coded by D. Kitamura (d-kitamura@ieee.org)
%
% Copyright 2018 Daichi Kitamura
%
% These programs are distributed only for academic research at
% universities and research institutions.
% It is not allowed to use or modify these programs for commercial or
% industrial purpose without our permission.
% When you use or modify these programs and write research articles,
% cite the following references:
%
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper)
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation unifying independent vector analysis and
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24,
% no. 9, pp. 1626-1641, September 2016.
%
% # Book chapter (The algorithm was renamed as "ILRMA")
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation with independent low-rank matrix analysis,"
% Audio Source Separation. Signals and Communication Technology.,
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018.
%
% See also:
% http://d-kitamura.net
% http://d-kitamura.net/demo-ILRMA_en.html
%
% [syntax]
% [Y, cost, W] = ILRMA(X)
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58 changes: 28 additions & 30 deletions ILRMA_readable.m
View file
@@ -1,34 +1,32 @@
function [Y, cost, W] = ILRMA_readable(X, type, It, nb, drawConv, normalize, W, T, V, Z)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Independent low-rank matrix analysis (ILRMA) %
% %
% Coded by D. Kitamura (d-kitamura@ieee.org) on 1 Apr, 2018 (ver1.0). %
% %
% Copyright 2018 Daichi Kitamura %
% %
% These programs are distributed only for academic research at %
% universities and research institutions. %
% It is not allowed to use or modify these programs for commercial or %
% industrial purpose without our permission. %
% When you use or modify these programs and write research articles, %
% cite the following references: %
% %
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper) %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation unifying independent vector analysis and %
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24, %
% no. 9, pp. 1626-1641, September 2016. %
% %
% # Book chapter (The algorithm was renamed as "ILRMA") %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation with independent low-rank matrix analysis," %
% Audio Source Separation. Signals and Communication Technology., %
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018. %
% %
% See also: %
% http://d-kitamura.net %
% http://d-kitamura.net/en/demo_rank1_en.htm %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Independent low-rank matrix analysis (ILRMA)
%
% Coded by D. Kitamura (d-kitamura@ieee.org)
%
% Copyright 2018 Daichi Kitamura
%
% These programs are distributed only for academic research at
% universities and research institutions.
% It is not allowed to use or modify these programs for commercial or
% industrial purpose without our permission.
% When you use or modify these programs and write research articles,
% cite the following references:
%
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper)
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation unifying independent vector analysis and
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24,
% no. 9, pp. 1626-1641, September 2016.
%
% # Book chapter (The algorithm was renamed as "ILRMA")
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation with independent low-rank matrix analysis,"
% Audio Source Separation. Signals and Communication Technology.,
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018.
%
% See also:
% http://d-kitamura.net
% http://d-kitamura.net/demo-ILRMA_en.html
%
% [syntax]
% [Y, cost, W] = ILRMA(X)
Expand Down
62 changes: 30 additions & 32 deletions backProjection.m
View file
@@ -1,36 +1,34 @@
function [Z] = backProjection(Y, X)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Back projection technique for fixing the frequency-wise scales of the %
% signals estimated by ICA-based blind source separation techniques. %
% Both monaural and multichannel outputs are supported. %
% %
% Coded by D. Kitamura (d-kitamura@ieee.org) on 1 Apr, 2018 (ver1.0). %
% %
% Copyright 2018 Daichi Kitamura %
% %
% These programs are distributed only for academic research at %
% universities and research institutions. %
% It is not allowed to use or modify these programs for commercial or %
% industrial purpose without our permission. %
% When you use or modify these programs and write research articles, %
% cite the following references: %
% %
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper) %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation unifying independent vector analysis and %
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24, %
% no. 9, pp. 1626-1641, September 2016. %
% %
% # Book chapter (The algorithm was renamed as "ILRMA") %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation with independent low-rank matrix analysis," %
% Audio Source Separation. Signals and Communication Technology., %
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018. %
% %
% See also: %
% http://d-kitamura.net %
% http://d-kitamura.net/en/demo_rank1_en.htm %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Back projection technique for fixing the frequency-wise scales of the
% signals estimated by ICA-based blind source separation techniques.
% Both monaural and multichannel outputs are supported.
%
% Coded by D. Kitamura (d-kitamura@ieee.org)
%
% Copyright 2018 Daichi Kitamura
%
% These programs are distributed only for academic research at
% universities and research institutions.
% It is not allowed to use or modify these programs for commercial or
% industrial purpose without our permission.
% When you use or modify these programs and write research articles,
% cite the following references:
%
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper)
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation unifying independent vector analysis and
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24,
% no. 9, pp. 1626-1641, September 2016.
%
% # Book chapter (The algorithm was renamed as "ILRMA")
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation with independent low-rank matrix analysis,"
% Audio Source Separation. Signals and Communication Technology.,
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018.
%
% See also:
% http://d-kitamura.net
% http://d-kitamura.net/demo-ILRMA_en.html
%
% [syntax]
% [Z, D] = backProjection(Y, X)
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60 changes: 29 additions & 31 deletions bss_ILRMA.m
View file
@@ -1,35 +1,33 @@
function [sep, cost] = bss_ILRMA(mix, ns, nb, fftSize, shiftSize, it, type, refMic, drawConv, normalize)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Blind source separation using independent low-rank matrix analysis %
% (ILRMA) %
% %
% Coded by D. Kitamura (d-kitamura@ieee.org) on 1 Apr, 2018 (ver1.0). %
% %
% Copyright 2018 Daichi Kitamura %
% %
% These programs are distributed only for academic research at %
% universities and research institutions. %
% It is not allowed to use or modify these programs for commercial or %
% industrial purpose without our permission. %
% When you use or modify these programs and write research articles, %
% cite the following references: %
% %
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper) %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation unifying independent vector analysis and %
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24, %
% no. 9, pp. 1626-1641, September 2016. %
% %
% # Book chapter (The algorithm was renamed as "ILRMA") %
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined %
% blind source separation with independent low-rank matrix analysis," %
% Audio Source Separation. Signals and Communication Technology., %
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018. %
% %
% See also: %
% http://d-kitamura.net %
% http://d-kitamura.net/en/demo_rank1_en.htm %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Blind source separation using independent low-rank matrix analysis
% (ILRMA)
%
% Coded by D. Kitamura (d-kitamura@ieee.org)
%
% Copyright 2018 Daichi Kitamura
%
% These programs are distributed only for academic research at
% universities and research institutions.
% It is not allowed to use or modify these programs for commercial or
% industrial purpose without our permission.
% When you use or modify these programs and write research articles,
% cite the following references:
%
% # Original paper (The algorithm was called "Rank-1 MNMF" in this paper)
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation unifying independent vector analysis and
% nonnegative matrix factorization," IEEE/ACM Trans. ASLP, vol. 24,
% no. 9, pp. 1626-1641, September 2016.
%
% # Book chapter (The algorithm was renamed as "ILRMA")
% D. Kitamura, N. Ono, H. Sawada, H. Kameoka, H. Saruwatari, "Determined
% blind source separation with independent low-rank matrix analysis,"
% Audio Source Separation. Signals and Communication Technology.,
% S. Makino, Ed. Springer, Cham, pp. 125-155, March 2018.
%
% See also:
% http://d-kitamura.net
% http://d-kitamura.net/demo-ILRMA_en.html
%
% [syntax]
% [sep, cost] = bss_ILRMA(mix, ns, nb, fftSize, shiftSize, it, type, draw, stable)
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4 changes: 2 additions & 2 deletions main.m
View file
Expand Up @@ -2,7 +2,7 @@
% Sample program for blind source separation using independent low-rank %
% matrix analysis (ILRMA) %
% %
% Coded by D. Kitamura (d-kitamura@ieee.org) on 1 Apr, 2018 (ver1.0). %
% Coded by D. Kitamura (d-kitamura@ieee.org) %
% %
% Copyright 2018 Daichi Kitamura %
% %
Expand All @@ -27,7 +27,7 @@
% %
% See also: %
% http://d-kitamura.net %
% http://d-kitamura.net/en/demo_rank1_en.htm %
% http://d-kitamura.net/demo-ILRMA_en.html %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

clear;
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