Random Sequence u(n) Generation and Analysis
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We can perform further analysis by generating a random sequence u(n). First, we compute the autocorrelation coefficients, which helps us understand the correlation between different elements in the sequence. This can be implemented using functions like xcorr() in MATLAB or correlation algorithms in Python's NumPy library. Second, we calculate the power spectrum density, which reveals the energy distribution across different frequency components in the sequence. This analysis is typically performed using Fast Fourier Transform (FFT) algorithms or periodogram methods. Through these analytical approaches, we can gain deeper insights into the characteristics and properties of the sequence, including its statistical behavior and frequency domain features.
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