MATLAB: How to generate noise from 950 to 1050 Hz for 0.2 sec

bbnFilter Design Toolboxnoise

How to generate noise from 950 to 1050 Hz for 0.2 sec? Please help me.

Best Answer

Choose Fs, generate broadband noise, filter with a bandpass:

Fs = 44100;
Tmax = 0.2;
Samples = Tmax*Fs;
noise   = randn(Samples,1);
noise = bandpass(noise,[950 1050],Fs);
pspectrum(noise,Fs)

Related Solutions

MATLAB: Generating pure tone and noise

See here for an excellent solution to generating your noise from one of your previous questions:

Generate noise

You can use the code from the previous answer I gave you to add a rise-fall time for 10 ms and the other stimulus.

the 10 dB SNR should also be the same. Example below.

%set-up parameters
fs=44100; %CD quality - also conveniently divisible by 30 and 25
stim_dur=.025; %duration of puretone in seconds
noise_dur=.200; %duration of noise in seconds
ISI_dur=.020; %ISI duration in seconds
ramp_dur=.010; %ramp duration in seconds
t=0:1/fs:stim_dur-1/fs;
f=1000;
%create noise
nsamples = floor(noise_dur*fs);
noise_all_Hz   = randn(nsamples,1);
noise = bandpass(noise_all_Hz,[950 1050],fs);
noise=noise';
%create 1000 Hz tone
xt=sin(2*pi*f*t);
%setup ramp
rampSamps = floor(fs*ramp_dur);
window=hanning(2*rampSamps)'; %hanning window is cosine^2 this will change depending on the kind of ramp you want
w1=window(1:ceil((length(window))/2)); %use the first half of hanning function for onramp
w2=window(ceil((length(window))/2)+1:end); %use second half of hanning function of off ramp
w_on_xt = [w1 ones(1,length(xt)-length(w1))];
w_off_xt = [ones(1,length(xt)-length(w2)) w2];
w_on_noise = [w1 ones(1,length(noise)-length(w1))];
w_off_noise = [ones(1,length(noise)-length(w2)) w2];
%ramp stimuli
noise_ramped = noise.*w_on_noise.*w_off_noise; 
xt_ramped = xt.*w_on_xt.*w_off_xt; 
% scale
rms_xt_ramped=rms(xt_ramped); %check the average intensity of the ramped 500 Hz signal
amp_10dB=10^(-10/20)*rms_xt_ramped; %find the new amplitude that is 10 dB lower
%normalize the xt2_ramped stimulus and then scale to -10 dB
noise_ramped_norm=noise_ramped./rms(noise_ramped);
noise_ramped_10dB=noise_ramped_norm.*amp_10dB;
%check
rms_noise_ramped=rms(noise_ramped_10dB);
20*log10(rms_xt_ramped/rms_noise_ramped)
%generate ISI
ISI=zeros(ISI_dur*fs,1);
%final stimulus
out=[noise_ramped_10dB';ISI;xt_ramped'];
plot(out)
sound(out,fs)

MATLAB: How to only pass the signals that I want

hello

this code will do fft / spectrogram and bandpass filtering - adapt the corner frequencies to your own needs !

clc
clear all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%





% FFT parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
NFFT = 4096;    % 
OVERLAP = 0.5;
% spectrogram dB scale
spectrogram_dB_scale = 80;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% options 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% if you are dealing with acoustics, you may wish to have A weighted
% spectrums 
% option_w = 0 : linear spectrum (no weighting dB (L) )
% option_w = 1 : A weighted spectrum (dB (A) )
option_w = 1;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% load signal
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% data
% [data,Fs] = audioread('myWAVaudiofile.wav');
[data,Fs] = audioread('Immigran_Hiss.wav');
channel = 1;
signal = data(:,channel);
samples = length(signal);
%% decimate (if needed)
% NB : decim = 1 will do nothing (output = input)
decim = 1;
if decim>1
    signal = decimate(signal,decim);
    Fs = Fs/decim;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% display 1 : averaged FFT spectrum
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[freq, sensor_spectrum] = myfft_peak(signal,Fs,NFFT,OVERLAP);
% convert to dB scale (ref = 1)
sensor_spectrum_dB = 20*log10(sensor_spectrum);
% apply A weigthing if needed


if option_w == 1
    pondA_dB = pondA_function(freq);
    sensor_spectrum_dB = sensor_spectrum_dB+pondA_dB;
    my_ylabel = ('Amplitude (dB (A))');
else
    my_ylabel = ('Amplitude (dB (L))');
end
figure(1),plot(freq,sensor_spectrum_dB,'b');grid
title(['Averaged FFT Spectrum  / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(freq(2)-freq(1)) ' Hz ']);
xlabel('Frequency (Hz)');ylabel(my_ylabel);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%



% display 2 : time / frequency analysis : spectrogram demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[sg,fsg,tsg] = specgram(signal,NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));  
% FFT normalisation and conversion amplitude from linear to dB (peak)

sg_dBpeak = 20*log10(abs(sg))+20*log10(2/length(fsg));     % NB : X=fft(x.*hanning(N))*4/N; % hanning only

% apply A weigthing if needed
if option_w == 1
    pondA_dB = pondA_function(fsg);
    sg_dBpeak = sg_dBpeak+(pondA_dB*ones(1,size(sg_dBpeak,2)));
    my_title = ('Spectrogram (dB (A))');
else
    my_title = ('Spectrogram (dB (L))');
end
% saturation of the dB range : 

% saturation_dB = 60;  % dB range scale (means , the lowest displayed level is XX dB below the max level)

min_disp_dB = round(max(max(sg_dBpeak))) - spectrogram_dB_scale;
sg_dBpeak(sg_dBpeak<min_disp_dB) = min_disp_dB;
% plots spectrogram

figure(2);
imagesc(tsg,fsg,sg_dBpeak);colormap('jet');
axis('xy');colorbar('vert');grid
title([my_title ' / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(fsg(2)-fsg(1)) ' Hz ']);
xlabel('Time (s)');ylabel('Frequency (Hz)');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% removal of hiss between t = 0 and t = 1.68 s
% use of bandpass filter to remove noise below 500 and above 2500 Hz
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
data_filtered = data;
t_min = 0;
t_max = 1.68;
ind = 1+fix(t_min*Fs:t_max*Fs-1);
% keep only signal content extracted by bandpass filters 
f_low = 500;
f_high = 2500;
N = 4;
% signal_filtered = zeros(size(signal));
[b,a] = butter(N,2/Fs*[f_low f_high]);
% now let's filter the signal
data_filtered(ind,:) = filtfilt(b,a,data(ind,:));
% save as wav file 
audiowrite('Immigran_Hiss-filt.wav',data_filtered,Fs);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% display 2B : time / frequency analysis : spectrogram demo
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[sg,fsg,tsg] = specgram(data_filtered(:,1),NFFT,Fs,hanning(NFFT),floor(NFFT*OVERLAP));  
% FFT normalisation and conversion amplitude from linear to dB (peak)
sg_dBpeak = 20*log10(abs(sg))+20*log10(2/length(fsg));     % NB : X=fft(x.*hanning(N))*4/N; % hanning only
% apply A weigthing if needed
if option_w == 1
    pondA_dB = pondA_function(fsg);
    sg_dBpeak = sg_dBpeak+(pondA_dB*ones(1,size(sg_dBpeak,2)));
    my_title = ('Spectrogram (dB (A))');
else
    my_title = ('Spectrogram (dB (L))');
end
% saturation of the dB range : 
% saturation_dB = 60;  % dB range scale (means , the lowest displayed level is XX dB below the max level)
min_disp_dB = round(max(max(sg_dBpeak))) - spectrogram_dB_scale;
sg_dBpeak(sg_dBpeak<min_disp_dB) = min_disp_dB;
% plots spectrogram
figure(3);
imagesc(tsg,fsg,sg_dBpeak);colormap('jet');
axis('xy');colorbar('vert');grid
title([my_title ' / Fs = ' num2str(Fs) ' Hz / Delta f = ' num2str(fsg(2)-fsg(1)) ' Hz ']);
xlabel('Time (s)');ylabel('Frequency (Hz)');
function pondA_dB = pondA_function(f)
	% dB (A) weighting curve
	n = ((12200^2*f.^4)./((f.^2+20.6^2).*(f.^2+12200^2).*sqrt(f.^2+107.7^2).*sqrt(f.^2+737.9^2)));
	r = ((12200^2*1000.^4)./((1000.^2+20.6^2).*(1000.^2+12200^2).*sqrt(1000.^2+107.7^2).*sqrt(1000.^2+737.9^2))) * ones(size(f));
	pondA = n./r;
	pondA_dB = 20*log10(pondA(:));
end
function  [freq_vector,fft_spectrum] = myfft_peak(signal, Fs, nfft, Overlap)
% FFT peak spectrum of signal  (example sinus amplitude 1   = 0 dB after fft).
% Linear averaging
%   signal - input signal, 
%   Fs - Sampling frequency (Hz).
%   nfft - FFT window size
%   Overlap - buffer overlap % (between 0 and 0.95)
samples = length(signal);
% fill signal with zeros if its length is lower than nfft
if samples<nfft
    s_tmp = zeros(nfft,1);
    s_tmp((1:samples)) = signal;
    signal = s_tmp;
    samples = nfft;
end
% window : hanning
window = hanning(nfft);
window = window(:);
%    compute fft with overlap 
 offset = fix((1-Overlap)*nfft);
 spectnum = 1+ fix((samples-nfft)/offset); % Number of windows
%     % for info is equivalent to : 
%     noverlap = Overlap*nfft;
%     spectnum = fix((samples-noverlap)/(nfft-noverlap));	% Number of windows
    % main loop
    fft_spectrum = 0;
    for i=1:spectnum
        start = (i-1)*offset;
        sw = signal((1+start):(start+nfft)).*window;
        fft_spectrum = fft_spectrum + (abs(fft(sw))*4/nfft);     % X=fft(x.*hanning(N))*4/N; % hanning only 
    end
    fft_spectrum = fft_spectrum/spectnum; % to do linear averaging scaling
% one sidded fft spectrum  % Select first half 
    if rem(nfft,2)    % nfft odd
        select = (1:(nfft+1)/2)';
    else
        select = (1:nfft/2+1)';
    end
fft_spectrum = fft_spectrum(select);
freq_vector = (select - 1)*Fs/nfft;
end

Best Answer

Related Solutions

MATLAB: Generating pure tone and noise

MATLAB: How to only pass the signals that I want

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