6. Let X(e2) be the DTFT of a signal nl which is known to be zero...
5. (4 pts) Let X(ej) be the DTFT of a signal x[n] which is known to be zero for n < 0 and n > 3. We know X(eja) for four values of N as follows. X(@j0) = 10, X(eja/2) = 5 – 5j, X(ejt) = 0, X(ej37/2) = 5 + 5j (a) (3 pts) Find x[n]. (Hint: Compute the IDFT) (b) (1 pts) Find X(ej?).
12. Let X(e") be the DTFT of the discrete-time signal z[n] = (0.5)"u[n]. Let gin] be the length-5 sequence whose 5-point DFT, Gk], is made from uniform samples from X(eu): g[n] CH 0 for n<0and n > 4 = x(e,2 ) for k = 0, 1, 2,3,4 = Find g(0] and gl1]. 12. Let X(e") be the DTFT of the discrete-time signal z[n] = (0.5)"u[n]. Let gin] be the length-5 sequence whose 5-point DFT, Gk], is made from uniform samples...
1.4. Let x[n] be a signal with x[n] = 0 for n < -2 and n > 4. For each signal given below, determine the values of n for which it is guaranteed to be zero. (a) xịn - 3] (b) x[n+ 4] (c) x[-n] (d) x[-n+2] (e) x[-n-2] 1.5. Let x(t) be a signal with x(t) = 0 for t <3. For each signal given below, determine the values of t for which it is guaranteed to be zero....
4. Let f(x) = 22xe-2x,x>> 0). Assume that we have a random sample of size n from this distribution. Find the maximum likelihood estimator of 2.
Let a periodic signal x(t) with a fundamental frequency ??e2? have a period 4.6 (a) Plot x(t), and indicate its fundamental period To (b) Compute the Fourier series coefficients of x(t) using their integral (c) (d) Answers: x(t) is periodic of fundamental period definition. Use the Laplace transform to compute the Fourier series coefficients Xk. Indicate how to compute the dc term. Suppose that y(t) = dx(t)/dt, find the Fourier transform of x(t) by means of the Fourier series coefficients...
For all parts of this problem, let z(t) be the signal shown below. (Note that x(t) is defined by: x(t) = 3 - t for 0 <t <3; (t) = 0, otherwise.) 3 x(t) to i à (a) (6 points) Find the values of: (i) ſo r(t)8(t – 1)dt (ii) x(t)(t – 1)dt. (b) (6 points) Plot the signal y(t) defined by y(t) = x(r – 2)8(t – r)dr. (c) (6 points) Find the energy in x(t). (d) (7 points)...
I will upvote if u will solve What u need? DFT can also be obtained using matrix multiplication. Let X[r] show the transformed values and x[n] show the original signal. Using the analysis equation: Using matrix multiplication, this operation can be written as x[O X[1 1 e(2m/N) e-K4n/N) x12] [N-1]] e-j(2(N-1)T/N)e-j(4(N-1)m/N) Instead of huilt-in EFT function use matrix multinlication to solve 3th auestion [ 1 e-/(2(N-1)(N-1)T/N)]Le[N-1] DFT is an extension of DTFT in which frequency is discretized to a finite...
6.72 Let Y =X+N where X and N are independent Gaussian random variables with different variance and N is zero mean. (a) Plot the correlation coefficient between the “observed signal” Y and the “desired signal” X as a funtion of the signal-to-noise ratio (b) Find the minimum mean square error estimator for X given Y (c)Find the MAP and ML estimators for X given Y (d) Compare the mean square error of the estimators in parts a, b, and c.
6. Let Xc(r) = cos 2π450t. This signal is sampled with f, = 1 .5kHz: x[n] = xe (nT), n = 0,±1, . . . where T, = 1/f, we have 512 samples of x[n]. (a) Plot X (el") of x[n], n = 0, ± 1 , ±2, . . . (b) Approximately plot the DFT magnitude |x(kl. The DFT size is N = 512.
A causal filter H(z) is excited by x(n) which is a white noise signal of zero mean 2 and unit variance. Its output is y(n). (28 points) H(2)05 Z-0.9 Give the autocorrelation of y(n) in closed form. Show all your work Give numerical values for ryy(0).1(1).1(2) a. b. Give the variance of y(n). c. Give the power spectral density (PSD) of y(n). d. A causal filter H(z) is excited by x(n) which is a white noise signal of zero mean...