Hi all, Suppose my signal is a complex valued signal, and it is complex conjugated with respect to the center t=0. That's to say f(-t)=f(t)*, where "*" denotes the complex conjugate. Suppose now I do the truncation of above signal into between [-B, B), and I sample it using stepsize dB, then in Matlab, the sampling points are cfs=[-B:dB:B-dB], which has 2B/dB data points, e.g. -B, -B+dB, -B+2*dB, ... , 0, dB, 2*dB, ... B-dB. Let's assume 2B is divisable by dB. I found out that I have to do fftshift(cfs) before feeding into fft function, then I will obtain my desired output: so, output = fft(fftshift(cfs)), and the output are all real numbers. This is our desired output. Now I want to ask: is there some trick in FFT that I can use to further reduce computations? Let's say, since my output is going to be real, and my input is complex conjugate, is there a way to throw away the real part, and only do the FFT on the real part, or something like that? I saw somewhere on the web that there is a special program for real input and real output FFT which can be even faster than a standard complex FFT. Moreover, my input is complex conjugate, is there a way that I can throw away the f(t)'s for t<0, and thus only do fft on half of the orginal data sequence? Thanks a lot!
Is there a way to reduce the number of operations in this FFT procedure?
Started by ●August 9, 2007