%% Peak detection Part % In this part, we have defined a threshold value. So, all peaks above % threshold value will be detected. temp_fft = data_filt_ft; % Normalize the FFT temp_fft = temp_fft/max(temp_fft); % threshold th = 0.02; % i.e. 1% of maximum amplitude temp_fft(temp_fft < th) = 0; %you can skip this step by commenting this. % Plot FFT after thresholding figure; plot(fr, temp_fft); xlabel('Frequency(Hz)'); ylabel('Amplitude'); grid on; % find peaks of the remaining data [peak_ft, peak_loc] = findpeaks(temp_fft); % frequency corresponding to peak [peak_fr] = fr(peak_loc); %Sort amplitude values into descending order DescendAmp = sort(peak_ft,'descend'); % this fuction returns the fourier transform of the signal function [ft, f] = fr_t(x, Fs) L = length(x); % NFFT = 2^nextpow2(L); % Next power of 2 from length of y NFFT = L; X = fft(x,NFFT)/NFFT; f = Fs/2*linspace(0,1,floor(NFFT/2+1)); ft = abs(X(1:floor(NFFT/2+1))); % ft = 20*log10(ft); % plot(f,ft); end
clc %% dummy data Fs = 1e3; samples = 1e4; t = (0:samples-1)'*1/Fs; signal = 0.7*cos(2*pi*50*t)+0.4*cos(2*pi*100*t)+0.1*randn(samples,1); [data_filt_ft, fr] = fr_t(signal, Fs); %% Peak detection Part % In this part, we have defined a threshold value. So, all peaks above % threshold value will be detected. temp_fft = data_filt_ft; % Normalize the FFT temp_fft = temp_fft/max(temp_fft); % threshold th = 0.02; % i.e. 1% of maximum amplitude temp_fft(temp_fft < th) = 0; %you can skip this step by commenting this. % Plot FFT after thresholding figure; plot(fr, temp_fft); xlabel('Frequency(Hz)'); ylabel('Amplitude'); grid on; % find peaks of the remaining data [peak_ft, peak_loc] = findpeaks(temp_fft); %Sort amplitude values into ascending order [peak_ft_sorted_values,peak_ft_sorted_index] = sort(peak_ft,'ascend'); % frequency corresponding to peak [peak_fr] = fr(peak_loc); % and now sorted according to amplitude (above) peak_fr_sorted_values = peak_fr(peak_ft_sorted_index) % this fuction returns the fourier transform of the signal function [ft, f] = fr_t(x, Fs) L = length(x); % NFFT = 2^nextpow2(L); % Next power of 2 from length of y NFFT = L; X = fft(x,NFFT)/NFFT; f = Fs/2*linspace(0,1,floor(NFFT/2+1)); ft = abs(X(1:floor(NFFT/2+1))); % ft = 20*log10(ft); % plot(f,ft); end
Matlabsolutions.com provides guaranteed satisfaction with a
commitment to complete the work within time. Combined with our meticulous work ethics and extensive domain
experience, We are the ideal partner for all your homework/assignment needs. We pledge to provide 24*7 support
to dissolve all your academic doubts. We are composed of 300+ esteemed Matlab and other experts who have been
empanelled after extensive research and quality check.
Matlabsolutions.com provides undivided attention to each Matlab
assignment order with a methodical approach to solution. Our network span is not restricted to US, UK and Australia rather extends to countries like Singapore, Canada and UAE. Our Matlab assignment help services
include Image Processing Assignments, Electrical Engineering Assignments, Matlab homework help, Matlab Research Paper help, Matlab Simulink help. Get your work
done at the best price in industry.