I am an engineer by discipline, so I have a basic understanding of sine waves, but I am unfamiliar with signal processing techniques. I have two sets of noisy, irregularly sampled sinusoids and I have been tasked quantify how similar they are. The code below generates arrays that are similar to the data I am looking at. My data, however, was measured, so I have no prior knowledge of the amplitudes/frequencies of the sinusoids, only 3 arrays: one containing the discrete time points, and the other two containig the discrete values for signal x and signal y.
t = sort(10*rand(10000,1)); % Generate uneven sample times
x = 2*sin(pi*t) + 3*cos(2*pi*t) + rand(size(t)); % Generate signal 1
y = 2.1*sin(pi*t+0.3) + 3.1*cos(2*pi*t+0.3) + rand(size(t)); % Generate signal 2
I’d greatly appreciate any guidance/references to how to accomplish the task. Thank you for your time.I am an engineer by discipline, so I have a basic understanding of sine waves, but I am unfamiliar with signal processing techniques. I have two sets of noisy, irregularly sampled sinusoids and I have been tasked quantify how similar they are. The code below generates arrays that are similar to the data I am looking at. My data, however, was measured, so I have no prior knowledge of the amplitudes/frequencies of the sinusoids, only 3 arrays: one containing the discrete time points, and the other two containig the discrete values for signal x and signal y.
t = sort(10*rand(10000,1)); % Generate uneven sample times
x = 2*sin(pi*t) + 3*cos(2*pi*t) + rand(size(t)); % Generate signal 1
y = 2.1*sin(pi*t+0.3) + 3.1*cos(2*pi*t+0.3) + rand(size(t)); % Generate signal 2
I’d greatly appreciate any guidance/references to how to accomplish the task. Thank you for your time. I am an engineer by discipline, so I have a basic understanding of sine waves, but I am unfamiliar with signal processing techniques. I have two sets of noisy, irregularly sampled sinusoids and I have been tasked quantify how similar they are. The code below generates arrays that are similar to the data I am looking at. My data, however, was measured, so I have no prior knowledge of the amplitudes/frequencies of the sinusoids, only 3 arrays: one containing the discrete time points, and the other two containig the discrete values for signal x and signal y.
t = sort(10*rand(10000,1)); % Generate uneven sample times
x = 2*sin(pi*t) + 3*cos(2*pi*t) + rand(size(t)); % Generate signal 1
y = 2.1*sin(pi*t+0.3) + 3.1*cos(2*pi*t+0.3) + rand(size(t)); % Generate signal 2
I’d greatly appreciate any guidance/references to how to accomplish the task. Thank you for your time. fft, plomb, lomb, scargle, signal processing, discrete, discrete signal processing, dsp, fourier, irregular, noisy, irregularly sampled, noisy data, noisy sinusoid MATLAB Answers — New Questions

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