NO 5) Gaussian white noise with power spectral density function Sw (f) = and power spectral...

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NO 5) Gaussian white noise with power spectral density function Sw (f) = and power spectral density function Sx(f) = kf² which is 0 elsewhere, adds up. The signal s (t), which is the sum of the two signals, is applied to the ideal low-pass filter whose bandwidth B is B>W. Give values to the parameters No, k, B, W. After giving value to the parameters, find the SNR value of the signal y (t) at the filter output and - W <f <W; the signal x (t), SNRY ?. compare it to the SNR value of the s(t) signal at the filter input. SNRS Explain your solution in detail. NO 5) Gaussian white noise with power spectral density function Sw (f) = and power spectral density function Sx(f) = kf² which is 0 elsewhere, adds up. The signal s (t), which is the sum of the two signals, is applied to the ideal low-pass filter whose bandwidth B is B>W. Give values to the parameters No, k, B, W. After giving value to the parameters, find the SNR value of the signal y (t) at the filter output and - W <f <W; the signal x (t), SNRY ?. compare it to the SNR value of the s(t) signal at the filter input. SNRS Explain your solution in detail.