Computing Amplitude Spectrum and Phase Spectrum of Signals
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Applying Fast Fourier Transform (FFT) to signals to extract their amplitude spectrum and phase spectrum. This process involves converting time-domain signals into frequency-domain representations using algorithms like Cooley-Tukey FFT implementation. The amplitude spectrum, computed as the magnitude of complex FFT coefficients (typically using abs() function), reveals the strength of different frequency components. The phase spectrum, calculated through angle() or atan2() functions applied to imaginary and real parts, displays phase differences across frequencies. By analyzing these spectra using signal processing libraries (such as MATLAB's fft() or Python's numpy.fft), we can characterize signal properties, identify frequency distributions, and extract valuable information about signal behavior through spectral decomposition techniques.
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