Question 1

For signal sequence $s _ { i } = ( 5 , - 2,3 )$ and noise $S D \sigma _ { N } = 0.1$, the variance of $V$ equals $\sigma _ { V } { } ^ { 2 } =\_\_\_$$( x . x x )$

Accepted Answer

$E _ { s } = \sum s _ { i } ^ { 2 } = 38 . \quad \sigma _ { N } ^ { 2 } = 0.01 . \rightarrow \sigma _ { v } ^ { 2 } = \sigma _ { N } ^ { 2 } E _ { s } = 0.38$

Question 2

A processor is matched to signal si = (5,-2, 3).Compute V and the determined binary data value br
when Xi = (-3, 1, 6) is observed.

Accepted Answer

$V = \sum c _ { i } X _ { i } = 5 ( - 3 ) - 2 ( 1 ) + 3 ( 6 ) = - 15 - 2 + 18 = 1 . \quad V > 0 - > b _ { r } = 1$

Question 3

For signal sequence $\left. s _ { i } = ( 5 , - 2,3 ) \text { and SNR } = 20 \mathrm {~dB} \text {, the noise SD } \sigma _ { N } = \_\_\_\_ x x \right) \text {. }$

Accepted Answer

$E _ { s } = \sum s _ { i } ^ { 2 } = 38 . S N R _ { d B } = 10 \log _ { 10 } E _ { s } / \sigma _ { N } ^ { 2 } = 20 \rightarrow E _ { s } / \sigma _ { N } ^ { 2 } = 10 ^ { 2 } . \sigma _ { N } ^ { 2 } = 38 / 100 = 0.38 \rightarrow \sigma _ { N } = 0.62$

Question 4

A linear processor with coefficient set $c _ { i } = ( 5,3,1 )$ that observes the signal values $X _ { \mathrm { i } } = ( 3,2,1 )$ produces output V equal to_______.

Accepted Answer

The answer of A linear processor with coefficient set \(c...

Question 5

For signal sequence $s _ { i } = ( 5 , - 2,3 )$ the matched processor produces output value equal to V =_____.

Accepted Answer

The answer of For signal sequence \(s _ { i...

Question 6

For signal sequence $\mathrm { s } _ { \mathrm { i } } = ( 5 , - 2,3 )$ ) and noise SD $\sigma _ { \mathrm { N } } = 0.1$ , the SNR equals _____ (xx.x) dB.

Accepted Answer

The answer of For signal sequence \(\mathrm { s }...

For signal sequence $s _ { i } = ( 5 , - 2,3 )$ and noise $S D \sigma _ { N } = 0.1$ , the variance of $V$ equals $\sigma _ { V } { } ^ { 2 } =\_\_\_$ $( x . x x )$

A processor is matched to signal si = (5,-2, 3).Compute V and the determined binary data value br when Xi = (-3, 1, 6) is observed.

For signal sequence $\left. s _ { i } = ( 5 , - 2,3 ) \text { and SNR } = 20 \mathrm {~dB} \text {, the noise SD } \sigma _ { N } = \_\_\_\_ x x \right) \text {. }$

A linear processor with coefficient set $c _ { i } = ( 5,3,1 )$ that observes the signal values $X _ { \mathrm { i } } = ( 3,2,1 )$ produces output V equal to_______.

For signal sequence $s _ { i } = ( 5 , - 2,3 )$ the matched processor produces output value equal to V =_____.

For signal sequence $\mathrm { s } _ { \mathrm { i } } = ( 5 , - 2,3 )$ ) and noise SD $\sigma _ { \mathrm { N } } = 0.1$ , the SNR equals _____ (xx.x) dB.

Introduction

Sensors and Actuators

Combinational Logic Circuits

Sequential Logic Circuits

Converting Between Analog and Digital Signals

Modeling Random Data and Noise

Designing Signals for Multiple-Access Systems

Source Coding

Channel Coding

Data Networks

Symbology

Excel Best Practices

Filters

Exam 7: Detecting Data Signals in Noise

For signal sequence si=(5,−2,3)s _ { i } = ( 5 , - 2,3 )si​=(5,−2,3) and noise SDσN=0.1S D \sigma _ { N } = 0.1SDσN​=0.1 , the variance of VVV equals σV2=___\sigma _ { V } { } ^ { 2 } =\_\_\_σV​2=___(x.xx)( x . x x )(x.xx)

A processor is matched to signal si = (5,-2, 3).Compute V and the determined binary data value br when Xi = (-3, 1, 6) is observed.

For signal sequence si=(5,−2,3) and SNR =20 dB, the noise SD σN=____xx). \left. s _ { i } = ( 5 , - 2,3 ) \text { and SNR } = 20 \mathrm {~dB} \text {, the noise SD } \sigma _ { N } = \_\_\_\_ x x \right) \text {. }si​=(5,−2,3) and SNR =20 dB, the noise SD σN​=____xx).

A linear processor with coefficient set ci=(5,3,1)c _ { i } = ( 5,3,1 )ci​=(5,3,1) that observes the signal values Xi=(3,2,1)X _ { \mathrm { i } } = ( 3,2,1 )Xi​=(3,2,1) produces output V equal to_______.

For signal sequence si=(5,−2,3)s _ { i } = ( 5 , - 2,3 )si​=(5,−2,3) the matched processor produces output value equal to V =_____.

For signal sequence si=(5,−2,3)\mathrm { s } _ { \mathrm { i } } = ( 5 , - 2,3 )si​=(5,−2,3) ) and noise SD σN=0.1\sigma _ { \mathrm { N } } = 0.1σN​=0.1 , the SNR equals _____ (xx.x) dB.

Introduction

Sensors and Actuators

Combinational Logic Circuits

Sequential Logic Circuits

Converting Between Analog and Digital Signals

Modeling Random Data and Noise

Designing Signals for Multiple-Access Systems

Source Coding

Channel Coding

Data Networks

Symbology

Excel Best Practices

Filters

For signal sequence $s _ { i } = ( 5 , - 2,3 )$ and noise $S D \sigma _ { N } = 0.1$ , the variance of $V$ equals $\sigma _ { V } { } ^ { 2 } =\_\_\_$ $( x . x x )$

For signal sequence $\left. s _ { i } = ( 5 , - 2,3 ) \text { and SNR } = 20 \mathrm {~dB} \text {, the noise SD } \sigma _ { N } = \_\_\_\_ x x \right) \text {. }$

A linear processor with coefficient set $c _ { i } = ( 5,3,1 )$ that observes the signal values $X _ { \mathrm { i } } = ( 3,2,1 )$ produces output V equal to_______.

For signal sequence $s _ { i } = ( 5 , - 2,3 )$ the matched processor produces output value equal to V =_____.

For signal sequence $\mathrm { s } _ { \mathrm { i } } = ( 5 , - 2,3 )$ ) and noise SD $\sigma _ { \mathrm { N } } = 0.1$ , the SNR equals _____ (xx.x) dB.