1
GATE ECE 2016 Set 2
Numerical
+2
-0
A binary communication system makes use of the symbols “zero” and “one”. There are channel errors. Consider the following events:
$${x_0}$$ : a " zero " is transmitted
$${x_1}$$ : a " one " is transmitted
$${y_0}$$ : a " zero " is received
$${y_1}$$ : a " one " is received
$${x_0}$$ : a " zero " is transmitted
$${x_1}$$ : a " one " is transmitted
$${y_0}$$ : a " zero " is received
$${y_1}$$ : a " one " is received
The following probabilities are given:
$$P({x_0}) = \,{3 \over 4},\,\left( {\,\left. {{y_0}} \right|{x_0}} \right) = \,{1 \over 2},\,\,and\,P\,\,\left( {\,\left. {{y_0}} \right|{x_1}} \right) = \,{1 \over 2}$$.
The information in bits that you obtain when you learn which symbol has been received (while you know that a " zero " has been transmitted) is _____________
Your input ____
2
GATE ECE 2016 Set 1
Numerical
+2
-0
Consider a discreet memoryless source with alphabet $$S = \left\{ {{s_0},\,{s_1},\,{s_2},\,{s_3},\,{s_{4......}}} \right\}$$ and respective probabilities of occurrence $$P = \left\{ {{1 \over 2},\,{1 \over 4},\,{1 \over 8},\,{1 \over {16}},\,{1 \over {32}},......} \right\}$$. The entropy of the source (in bits) is__________.
Your input ____
3
GATE ECE 2016 Set 3
Numerical
+2
-0
A voice-grade AWGN (additive white Gaussian noise) telephone channel has a bandwidth of 4.0 kHz and two-sided noise power spectral density $${\eta \over 2} = 2.5\, \times \,{10^{ - 5}}$$ Watt per Hz. If information at the rate of 52 kbps is to be transmitted over this channel with arbitrarily small bit error rate, then the minimum bit energy $${E_b}$$ (in mJ/bit) necessary is ________________
Your input ____
4
GATE ECE 2014 Set 1
Numerical
+2
-0
A fair coin is tossed repeatedly until a 'Head' appears for the first time. Let L be the number of tosses to get this first 'Head'. The entropy H (L) in bits is _______________.
Your input ____
GATE ECE Subjects
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Control Systems
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Analog Circuits
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Discrete Fourier Transform and Fast Fourier Transform Discrete Time Signal Fourier Series Fourier Transform Continuous Time Signal Laplace Transform Fourier Transform Representation of Continuous Time Signal Fourier Series Transmission of Signal Through Continuous Time LTI Systems Miscellaneous Sampling Continuous Time Linear Invariant System Discrete Time Linear Time Invariant Systems Discrete Time Signal Z Transform Transmission of Signal Through Discrete Time Lti Systems
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