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1. For which of the following is R(T) an appropriate autocorrelation function?...
Use your knowledge of the relationship between spectral density and autocorrelation function in order to answer the following questions. Show your work for full credit. Determine the spectral density...
Use your knowledge of the relationship between spectral density and autocorrelation function in order to answer the following questions. Show your work for full credit. Determine the spectral density of a process with autocorrelation function Rx(t) = 3e-2t a) Determine the spectral density of a process with autocorrelation function Rx(t)-2 sinc(0.51) b) c) Determine the autocorrelation function of a process with spectral density Sx (f) 2 sinc2(f/2) 12 Determine the autocorrelation function ofa process with spectral density Sx(a)-A+ d)
Use...
1) Random Processes: Suppose that a wide-sense stationary Gaussian random process X (t) is input to the filter shown below. The autocorrelation function of X(t) is 2xx (r) = exp(-ary Y(t) X(t) Delay...
1) Random Processes: Suppose that a wide-sense stationary Gaussian random process X (t) is input to the filter shown below. The autocorrelation function of X(t) is 2xx (r) = exp(-ary Y(t) X(t) Delay a) (4 points) Find the power spectral density of the output random process y(t), ΦΥΥ(f) b) (1 points) What frequency components are not present in ΦYYU)? c) (4 points) Find the output autocorrelation function Фуу(r) d) (1 points) What is the total power in the output process...
I. The autocorrelation function of a random signal is R(r) !-ⓞrect rect a. Find the power...
I. The autocorrelation function of a random signal is R(r) !-ⓞrect rect a. Find the power spectral density of the signal. b. Plot the amplitude of the power spectral density with Matlab (Let Ts -2) c. Find the null-to-null bandpass bandwidth, and the 0-to-null baseband bandwidth (in terms of Ts).
Consider the RC circuit shown below. Assume that R=(0.1)2 and C=(0.1)F 3. R i(t) y (t)...
Consider the RC circuit shown below. Assume that R=(0.1)2 and C=(0.1)F 3. R i(t) y (t) x(t) The input to this circuit is given as x(t) s(t)+ny (t), where the noise component of input, n(t), is a sample function realization of white noise process with an autocorrelation function given by Rpx(t) 8(T), and s (t) cos(6Tt) is the signal component of input. IS(fOI df, where S( a. Find the power of the signal component of input, Ps is the Fourier...
Consider the RC circuit shown below. Assume that R=(0.1)2 and C=(0.1)F 3. R i(t) y (t)...
Consider the RC circuit shown below. Assume that R=(0.1)2 and C=(0.1)F 3. R i(t) y (t) x(t) The input to this circuit is given as x(t) s(t)+ny (t), where the noise component of input, n(t), is a sample function realization of white noise process with an autocorrelation function given by Rpx(t) 8(T), and s (t) cos(6Tt) is the signal component of input. IS(fOI df, where S( a. Find the power of the signal component of input, Ps is the Fourier...
1.x(t) =Aexp((-t^2)/T^2) (T>0) (a) Energy Spectral Density (b)Autocorrelation Function y(t)=x(t)cos(2m/t) (1) Energy spectral Density 1.x(t) =Aexp((-t^2)/T^2) (T>0) (a) Energy Spectral...
1.x(t) =Aexp((-t^2)/T^2) (T>0) (a) Energy Spectral Density (b)Autocorrelation Function y(t)=x(t)cos(2m/t) (1) Energy spectral Density
1.x(t) =Aexp((-t^2)/T^2) (T>0) (a) Energy Spectral Density (b)Autocorrelation Function y(t)=x(t)cos(2m/t) (1) Energy spectral Density
Let the signals x(t) and y(t) be the input and output signals to a differentiator, respectively....
Let the signals x(t) and y(t) be the input and output signals to a differentiator, respectively. x(t) do y(t) (a) Let the autocorrelation of the signal x(t) be R (T) and the autocorrelation of the signal y(t) be R (T). If y(t)= X, express R, (T) in terms of R. (T) dt (b) Assume R (T) = 5e and find the power in the output signal y(t). JA, \f}<B (c) Assume that the power spectral density (PSD) of x(t) is...
2. Let Y(t) = (x(0)+)(\pi) where X(t) is a Poisson process with autocorrelation function Rxx(t1, tz)...
2. Let Y(t) = (x(0)+)(\pi) where X(t) is a Poisson process with autocorrelation function Rxx(t1, tz) = tīta + min(tı, tz), and 6 ~ U(0,2%) is independent of X(t). a. Is X(t) W.S.S.? b. If so, find its power spectral density. [25]
g(t) Given the signal g(t) = cos(t)), (1) Using the frequency-shifting property, find Fourier Transform G(f)in...
g(t) Given the signal g(t) = cos(t)), (1) Using the frequency-shifting property, find Fourier Transform G(f)in "sinc" format. (2) Find the Energy Spectrum Density (ESD): Sgf) = 1G(f)12 (3) Find and sketch the Autocorrelation R,(t) by Wiener-Khintchine Theorem. -210 210
1. For signal v(t) = 1 + 2 8(t-3n), determine (a) (8%) drawing of v(t); (b)...
1. For signal v(t) = 1 + 2 8(t-3n), determine (a) (8%) drawing of v(t); (b) (7%) period; (c) (10%) Fourier series form III; (d) (5%) power spectral density function; (e) (5%) autocorrelation function; (f) (5%) total power; (g) (5%) total energy. vle)- t2t Sce- (a) vl)
Use your knowledge of the relationship between spectral density and autocorrelation function in order to answer the following questions. Show your work for full credit. Determine the spectral density of a process with autocorrelation function Rx(t) = 3e-2t a) Determine the spectral density of a process with autocorrelation function Rx(t)-2 sinc(0.51) b) c) Determine the autocorrelation function of a process with spectral density Sx (f) 2 sinc2(f/2) 12 Determine the autocorrelation function ofa process with spectral density Sx(a)-A+ d)
Use...
1) Random Processes: Suppose that a wide-sense stationary Gaussian random process X (t) is input to the filter shown below. The autocorrelation function of X(t) is 2xx (r) = exp(-ary Y(t) X(t) Delay a) (4 points) Find the power spectral density of the output random process y(t), ΦΥΥ(f) b) (1 points) What frequency components are not present in ΦYYU)? c) (4 points) Find the output autocorrelation function Фуу(r) d) (1 points) What is the total power in the output process...
I. The autocorrelation function of a random signal is R(r) !-ⓞrect rect a. Find the power spectral density of the signal. b. Plot the amplitude of the power spectral density with Matlab (Let Ts -2) c. Find the null-to-null bandpass bandwidth, and the 0-to-null baseband bandwidth (in terms of Ts).
Consider the RC circuit shown below. Assume that R=(0.1)2 and C=(0.1)F 3. R i(t) y (t) x(t) The input to this circuit is given as x(t) s(t)+ny (t), where the noise component of input, n(t), is a sample function realization of white noise process with an autocorrelation function given by Rpx(t) 8(T), and s (t) cos(6Tt) is the signal component of input. IS(fOI df, where S( a. Find the power of the signal component of input, Ps is the Fourier...
Consider the RC circuit shown below. Assume that R=(0.1)2 and C=(0.1)F 3. R i(t) y (t) x(t) The input to this circuit is given as x(t) s(t)+ny (t), where the noise component of input, n(t), is a sample function realization of white noise process with an autocorrelation function given by Rpx(t) 8(T), and s (t) cos(6Tt) is the signal component of input. IS(fOI df, where S( a. Find the power of the signal component of input, Ps is the Fourier...
1.x(t) =Aexp((-t^2)/T^2) (T>0) (a) Energy Spectral Density (b)Autocorrelation Function y(t)=x(t)cos(2m/t) (1) Energy spectral Density
1.x(t) =Aexp((-t^2)/T^2) (T>0) (a) Energy Spectral Density (b)Autocorrelation Function y(t)=x(t)cos(2m/t) (1) Energy spectral Density
Let the signals x(t) and y(t) be the input and output signals to a differentiator, respectively. x(t) do y(t) (a) Let the autocorrelation of the signal x(t) be R (T) and the autocorrelation of the signal y(t) be R (T). If y(t)= X, express R, (T) in terms of R. (T) dt (b) Assume R (T) = 5e and find the power in the output signal y(t). JA, \f}<B (c) Assume that the power spectral density (PSD) of x(t) is...
2. Let Y(t) = (x(0)+)(\pi) where X(t) is a Poisson process with autocorrelation function Rxx(t1, tz) = tīta + min(tı, tz), and 6 ~ U(0,2%) is independent of X(t). a. Is X(t) W.S.S.? b. If so, find its power spectral density. [25]
g(t) Given the signal g(t) = cos(t)), (1) Using the frequency-shifting property, find Fourier Transform G(f)in "sinc" format. (2) Find the Energy Spectrum Density (ESD): Sgf) = 1G(f)12 (3) Find and sketch the Autocorrelation R,(t) by Wiener-Khintchine Theorem. -210 210
1. For signal v(t) = 1 + 2 8(t-3n), determine (a) (8%) drawing of v(t); (b) (7%) period; (c) (10%) Fourier series form III; (d) (5%) power spectral density function; (e) (5%) autocorrelation function; (f) (5%) total power; (g) (5%) total energy. vle)- t2t Sce- (a) vl)
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