This is based upon the white noise generation and narrow band through Matlab coding into mp3 file . %% write a code for white noise (1khz-16khz) and one narrow band sound (1khz-2khz)

low_f1 = 1000; % lower limit of the fq range high_f1 = 16000; % upper limit of the fq range fs = 33000; % sampling frequency time = 15; % in seconds len = 15; % in seconds

%% geberate a gaussian white signal n = round(time*fs); % number of samples x = randn(n ,1);

%% band pass the white noise to get the narrow band y = bandpass(x, [low_f1 high_f1],fs); [p, f] = pwelch(y, 1024, 768, 1024, fs);

%% read/generate sound f_sig1 = 1000; % lower limit of the fq range f_sig2 = 2000; % upper limit of the fq range t = linspace(0, len, fstime); % time Vector signal = sin(2pif_sig1t) + t.cos(2pif_sig2t) + 2sin(2pif_sig11.5*t);

% reading audio from sound_input.mp3 % [signal,fsig] = audioread('sound_input.mp3'); % reading signal

%% band pass the sound to get the narrow band sig_bp = bandpass(signal, [f_sig1 f_sig2],fs); [sig_nb, f_sig_nb] = pwelch(sig_bp, 1024, 768, 1024, fs);

%% plotting PSD subplot(2,1,1); plot(f, 10*log10(p))

subplot(2,1,2); plot(f_sig_nb, 10*log10(sig_nb))

%% write audio file - output.wav signal_final = y' + sig_bp(1:size(y,1)); sound(signal_final,fs) audiowrite('output.wav',signal_final,fs)