Mixing
Non-Wide-Sense-Stationary process with autocorrelation that depends on time shift
$begingroup$
My question consists of two parts.
1)
A wide sense stationary process has two properties:
a) it's mean is constant.
b) it's autocorrelation function depends on the time shift only.
My problem is that I can't think of a non wide sense stationary process that has the second condition(b) but not the first(a)
2)
Is the limit of the autocorrelation as the time shift approaches infinity is the square of the mean of the process? Is there a proof for this?
probability-theory stochastic-processes signal-processing
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
$endgroup$
add a comment |
$begingroup$
My question consists of two parts.
1)
A wide sense stationary process has two properties:
a) it's mean is constant.
b) it's autocorrelation function depends on the time shift only.
My problem is that I can't think of a non wide sense stationary process that has the second condition(b) but not the first(a)
2)
Is the limit of the autocorrelation as the time shift approaches infinity is the square of the mean of the process? Is there a proof for this?
probability-theory stochastic-processes signal-processing
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
$endgroup$
add a comment |
$begingroup$
My question consists of two parts.
1)
A wide sense stationary process has two properties:
a) it's mean is constant.
b) it's autocorrelation function depends on the time shift only.
My problem is that I can't think of a non wide sense stationary process that has the second condition(b) but not the first(a)
2)
Is the limit of the autocorrelation as the time shift approaches infinity is the square of the mean of the process? Is there a proof for this?
probability-theory stochastic-processes signal-processing
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
$endgroup$
My question consists of two parts.
1)
A wide sense stationary process has two properties:
a) it's mean is constant.
b) it's autocorrelation function depends on the time shift only.
My problem is that I can't think of a non wide sense stationary process that has the second condition(b) but not the first(a)
2)
Is the limit of the autocorrelation as the time shift approaches infinity is the square of the mean of the process? Is there a proof for this?
probability-theory stochastic-processes signal-processing
probability-theory stochastic-processes signal-processing
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
edited Jan 13 at 19:13
Kareem Metwaly
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
asked Jan 13 at 5:12
Kareem MetwalyKareem Metwaly
935
935
add a comment |
add a comment |
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