From 0136b3a9110b7ecb26c54557ad42b47e8ac3a410 Mon Sep 17 00:00:00 2001
From: Marina Kreme <amamarinak@gmail.com>
Date: Sun, 22 Nov 2020 06:11:59 +0100
Subject: [PATCH] doc
---
matlab/tfgm/tf_fading/compute_decomposition.m | 6 ++----
.../compute_decomposition_fixed_rank.m | 4 ++--
matlab/tfgm/tf_fading/compute_estimate.m | 2 +-
matlab/tfgm/tf_fading/compute_lambda.m | 8 +++++---
.../tf_fading/compute_lambda_oracle_sdr.m | 4 ++++
.../tfgm/tf_fading/estimate_energy_in_mask.m | 12 +++++------
matlab/tfgm/tf_fading/obj_fun.m | 20 ++++++++++---------
7 files changed, 31 insertions(+), 25 deletions(-)
diff --git a/matlab/tfgm/tf_fading/compute_decomposition.m b/matlab/tfgm/tf_fading/compute_decomposition.m
index b769ed9..e364f74 100644
--- a/matlab/tfgm/tf_fading/compute_decomposition.m
+++ b/matlab/tfgm/tf_fading/compute_decomposition.m
@@ -9,8 +9,8 @@ function [t_arrf,t_evdn, t_ut_x, rank_q, s_vec_list, u_mat_list,...,
%
% Inputs:
% - x_mix: mixtures of signals with wideband and localized spectrograms
-% -mask_list: list of mask
-% -gabmul_list: list of Gabor multiplier associated to each mask
+% -mask_list: cell of time -frequency mask
+% -gabmul_list: cell of Gabor multiplier associated to each mask
% - tolerance_arrf: tolearance. see [1]
% - proba_arrf: probability of success. see[1]
% Outputs:
@@ -34,11 +34,9 @@ function [t_arrf,t_evdn, t_ut_x, rank_q, s_vec_list, u_mat_list,...,
sig_len = length(x_mix);
-
n_areas = length(mask_list);
r = compute_r(sig_len, sig_len, proba_arrf);
-
%%
t_arrf = zeros(n_areas,1);
diff --git a/matlab/tfgm/tf_fading/compute_decomposition_fixed_rank.m b/matlab/tfgm/tf_fading/compute_decomposition_fixed_rank.m
index 5bc3b49..0f0a1db 100644
--- a/matlab/tfgm/tf_fading/compute_decomposition_fixed_rank.m
+++ b/matlab/tfgm/tf_fading/compute_decomposition_fixed_rank.m
@@ -8,8 +8,8 @@ function [t_rrf,t_evdn, t_ut_x, s_vec_list, u_mat_list,...,
%
% Inputs:
% - x_mix: mixtures of signals with wideband and localized spectrograms
-% -mask_list: list of mask
-% -gabmul_list: list of Gabor multiplier associated to each mask
+% -mask_list: cell of time-frequency mask
+% -gabmul_list: cell of Gabor multiplier associated to each mask
% - rank : matrix rank see [1]
% Outputs:
% -t_rrf: time for randomized range finder(rrf)
diff --git a/matlab/tfgm/tf_fading/compute_estimate.m b/matlab/tfgm/tf_fading/compute_estimate.m
index 89b3546..e271009 100644
--- a/matlab/tfgm/tf_fading/compute_estimate.m
+++ b/matlab/tfgm/tf_fading/compute_estimate.m
@@ -35,7 +35,7 @@ end
x = x_mix;
for k= 1:n_areas
- gamma_vec = lambda_coef(k)*s_vec_list{k}./(1-(1-lambda_coef(k))*s_vec_list{k});
+ gamma_vec = lambda_coef(k)*s_vec_list{k}./(1-(1-lambda_coef(k)).*s_vec_list{k});
x =x-u_mat_list{k}*(gamma_vec.*ut_x_list{k});
end
diff --git a/matlab/tfgm/tf_fading/compute_lambda.m b/matlab/tfgm/tf_fading/compute_lambda.m
index b9cbfeb..88a98f6 100644
--- a/matlab/tfgm/tf_fading/compute_lambda.m
+++ b/matlab/tfgm/tf_fading/compute_lambda.m
@@ -2,9 +2,11 @@ function [lambda_est, t_est] = compute_lambda(x_mix, mask, dgt_params,...,
signal_params, dgt, s_vec_list, u_mat_list, ut_x_list,...,
gabmul_list, fig_dir, e_target)
-%% [lambda_est, t_est] = compute_lambda(x_mix, mask, dgt_params, signal_params, dgt, s_vec_list, u_mat_list, ut_x_list,gabmul_list, fig_dir, e_target)
-
-% This function calculates lambda in algorithmes proposed in [1]
+%% [lambda_est, t_est] = compute_lambda(x_mix, mask, dgt_params,...,
+% signal_params, dgt, s_vec_list, u_mat_list, ut_x_list,...,
+% gabmul_list, fig_dir, e_target)
+% This function estimates the hyperparameters $\lambda$ from target energy
+% in each sub-region as we proposed in [1].
%
% Inputs:
% -x_mix:mixtures of signals with wideband and localized spectrograms
diff --git a/matlab/tfgm/tf_fading/compute_lambda_oracle_sdr.m b/matlab/tfgm/tf_fading/compute_lambda_oracle_sdr.m
index f85f783..dc0d078 100644
--- a/matlab/tfgm/tf_fading/compute_lambda_oracle_sdr.m
+++ b/matlab/tfgm/tf_fading/compute_lambda_oracle_sdr.m
@@ -2,6 +2,10 @@ function [lambda_oracle, t_oracle] = compute_lambda_oracle_sdr(n_areas, x_wb, x_
%% [lambda_oracle, t_oracle] = compute_lambda_oracle_sdr(n_areas,x_wb, x_rec)
% Function that calculates the estimated lambda using the true energy. see[1]
+% Compute oracle value for hyperparameter $\lambda_k$ from true solution.
+%
+% If only one region is considered, *fmincon* is used.
+% If multiple sub-regions are considered *fminbnd* is used
%
% Inputs:
% - n_areas: number of regions in mask
diff --git a/matlab/tfgm/tf_fading/estimate_energy_in_mask.m b/matlab/tfgm/tf_fading/estimate_energy_in_mask.m
index 2232cd0..285ddbc 100644
--- a/matlab/tfgm/tf_fading/estimate_energy_in_mask.m
+++ b/matlab/tfgm/tf_fading/estimate_energy_in_mask.m
@@ -1,7 +1,7 @@
function estimated_energy = estimate_energy_in_mask(x_mix, mask, dgt_params, signal_params, dgt,fig_dir)
%%estimated_energy = estimate_energy_in_mask(x_mix, mask, dgt_params, signal_params, dgt,fig_dir)
-% Functions that estimates energy in the mask
+% Functions that estimates energy in time-frequency mask
%
% Inputs:
% - x_mix:mixtures of signals with wideband and localized spectrograms
@@ -11,7 +11,7 @@ function estimated_energy = estimate_energy_in_mask(x_mix, mask, dgt_params, sig
% - dgt: Gabor transform operator
% - fig_dir: firgures directory
% Outputs:
-% -estimated_energy:estimated energy
+% -estimated_energy: Estimated energy in each sub-region.
%
%
% Author: Marina KREME
@@ -54,7 +54,7 @@ figure;
plotdgtreal(sqrt(e_mat), dgt_params.hop, dgt_params.nbins, fs, 'clim', clim);
%title(['Mask filled with average energy (total: ', num2str(estimated_energy,8),')']);
set(gca, 'FontSize', 20, 'fontName','Times');
-saveas(gcf,fullfile(fig_dir, 'filled_mask.pdf'));
+saveas(gcf,fullfile(fig_dir, 'mask_filled__with_energy.pdf'));
%
@@ -64,7 +64,7 @@ figure;
plotdgtreal(x_tf_mat, dgt_params.hop, dgt_params.nbins, fs, 'clim', clim);
%title(['Mix filled with average energy (total: ', num2str(estimated_energy,8),')']);
set(gca, 'FontSize', 20, 'fontName','Times');
-saveas(gcf,fullfile(fig_dir, 'filled_mask.pdf'));
+saveas(gcf,fullfile(fig_dir, 'filled_mix_with_average_energy.pdf'));
%
@@ -75,7 +75,7 @@ ylabel('Average energy')
grid on;
title('Average energy per frequency bin in mix');
set(gca, 'FontSize', 20, 'fontName','Times');
-saveas(gcf,fullfile(fig_dir, 'average_energy.pdf'));
+saveas(gcf,fullfile(fig_dir, 'average_energy_per_freq_bin.pdf'));
%%
@@ -89,7 +89,7 @@ title('Average energy per frequency bin in mix')
legend('Before filling', 'After filling')
grid on;
set(gca, 'FontSize', 20, 'fontName','Times');
-saveas(gcf,fullfile(fig_dir, 'average_energy_check.pdf'));
+saveas(gcf,fullfile(fig_dir, 'average_energy_per_freq_bin_mix.pdf'));
end
diff --git a/matlab/tfgm/tf_fading/obj_fun.m b/matlab/tfgm/tf_fading/obj_fun.m
index 369be32..0734fc6 100644
--- a/matlab/tfgm/tf_fading/obj_fun.m
+++ b/matlab/tfgm/tf_fading/obj_fun.m
@@ -1,10 +1,12 @@
function f_lambda = obj_fun(lambda_coef, x_mix, s_vec_list, ...,
u_mat_list, ut_x_list, mask, gab_mul, dgt, e_target)
-%% f_lambda = obj_fun(lambda_coef, x_mix, s_vec_list,u_mat_list, ut_x_list, mask, gab_mul, dgt, e_target)
-% Objecitve function for finding optimal lambda value in algorithms
+%% f_lambda = obj_fun(lambda_coef, x_mix, s_vec_list, ...,
+% u_mat_list, ut_x_list, mask, gab_mul, dgt, e_target)
+%
+% Objecitve function for finding optimal lambda value in algorithms
% proppsed in [1]
-%
+%
% Inputs:
% -lambda_coef: hyperparameters
% - x_mix: mixtures of signals with wideband and localized spectrograms
@@ -15,16 +17,16 @@ function f_lambda = obj_fun(lambda_coef, x_mix, s_vec_list, ...,
% - gab_mul:Gabor multiplier
% - dgt: Gabor transform operator
% - e_target: estimated energy in Omega region
-%
+%
% Output:
% - f_lambda: objective function
-%
-%
-%
+%
+%
+%
% Reference:
% [1]Time-frequency fading algorithms based on Gabor multipliers,2020.
-%
-%
+%
+%
% Author: Marina KREME
%%
x =compute_estimate(lambda_coef, x_mix, s_vec_list, u_mat_list, ut_x_list);
--
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