I think this is close to what you are looking for.
% % This code will generate a saltatory stimulus of 10 Hz up to 800 Hrz (the stimulus was frequency filtered in audacity to exclude frequencies bellow 80 and above 1000Hz)
duration = 80;
freq_step = 10;
sampling_rate = 44100;
% Generate the time samples
t = linspace(0, duration, sampling_rate * duration);
%generation of the audiowave with the increasing frequency steps
freq_range = freq_step * (0:length(t)-1) / sampling_rate;
audio_waveform = 0.5*sin(pi * freq_range.* t);
audio_waveform(1:(8*sampling_rate)) = [];
%normalization of the audiowave form
%audio_waveform = audio_waveform / max(abs(audio_waveform)); %this
%commented
%eliminate the normalization of the wave form
%create the audioplayer object
% player = audioplayer(audio_waveform, sampling_rate);
%play(player);
%save the file as WAV file format
% audiowrite("output_sound1.wav", audio_waveform, sampling_rate);
m = islocalmax(audio_waveform); % find indexes of the signal peaks
t_plot = t; % make a copy of the time vector to use for plotting
t_plot(1:(8*sampling_rate)) = []; % truncate the time vector the same way the audio_waveform was truncated
f = 1 ./ diff(t_plot(m)); % frequency is inverse of time between signal peaks
t_plot = t_plot(m); % extract the time at each of the peaks
% whos
plot(t_plot(2:end), f); % skip first time point since diff reduces vector length by one
grid on
xlabel('Time (sec)')
ylabel('Frequency (Hz)')
