81.
A unit impulse function δ(t) is defined by
1. δ(t) = 0 for all t except t = 0
2. $$\int_{ - \infty }^\infty {\delta \left( t \right)dt = 1} $$
The Fourier transform F(ω) of δ(t) is

82.
Consider an LTI system subjected to a wide sense stationary input {x(n)}, which is a white noise sequence. The cross correlation Φxy[m] between input x(n) and output y(n) is:
Where Φxx[m] = $$\sigma _{\text{x}}^2\delta \left[ {\text{m}} \right]$$  and h[.] is impulse response

84.
Let x(n) be a real-valued sequence that is a sample sequence of a wide-sense stationary discrete-time random process. The power density of this signal is

86.
If the input x(t) = u(t) + u(t - 1) is applied to a LTI system whose impulse response is given by h(t) = δ(t), then the response of the system y(t) is

88.
Let $$X\left( {{e^{j\omega }}} \right) = \sum\nolimits_{n = - \infty }^\infty {x\left[ n \right]{e^{ - j\omega n}}} $$      and $$x\left[ n \right] = \frac{1}{{2\pi }}\int\limits_{ - \pi }^\pi {X\left( {{e^{j\omega }}} \right){e^{j\omega n}}d\omega } .$$
If $$X\left( {{e^{j\omega }}} \right) = \frac{1}{{\left( {1 - 0.2{e^{ - j\omega }}} \right)\left( {1 - 0.1{e^{ - j\omega }}} \right)}},$$       what is x[n] in terms of unit discrete step function u(n)?

89.
Sampling theorem denoted as

90.
Given $$\mathop y\limits^{..} \left( t \right) + 3\mathop y\limits^. \left( t \right) + 4y\left( t \right) = 2\mathop x\limits^{..} \left( t \right) + 7\mathop x\limits^. \left( t \right) + 8x\left( t \right)$$
Then H(s) is given by

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