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What is the precise definition of a nonlinear signal?
Planned maintenance scheduled April 23, 2019 at 23:30 UTC (7:30pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?Causal question on a discrete signalHow to find phase values on precise pixel locations of a given Image?Getting the frequency of a 0.33Hz to 3Hz signalExact definition of soft bits in digital receiverDefinition of energy of a signalWhat subclass of nonlinear systems can be represented by Volterra series?What function to apply to a signal to expose its burstiness (i.e., make the burst part more evident than the non-bursty part)What is the type of these signals?Understanding the definition of signal's bandwidthWhat is the signal-noise model of laser induced fluorescence?
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I tried to find the the precise definition of a nonlinear signal. However it is not easy. How can we define a nonlinear signal?
signal-analysis
New contributor
$endgroup$
|
show 1 more comment
$begingroup$
I tried to find the the precise definition of a nonlinear signal. However it is not easy. How can we define a nonlinear signal?
signal-analysis
New contributor
$endgroup$
2
$begingroup$
Do you really mean a nonlinear signal? Or maybe a nonlinear system?
$endgroup$
– Max
Apr 18 at 7:46
$begingroup$
I mean a nonlinear signal.
$endgroup$
– cabal
Apr 18 at 10:08
$begingroup$
@cabal: The term really doesn't make much sense. Can you provide a reference where it's being used or did you come up with it yourself?
$endgroup$
– Hilmar
Apr 18 at 10:46
$begingroup$
I found it in "Encyclopedia of Information Science and Technology". Here is the link to the definition: igi-global.com/dictionary/…
$endgroup$
– cabal
Apr 18 at 10:50
$begingroup$
Well, the definition is there. A signal, that comes out of a nonlinear system. Refer to Matt's answer.
$endgroup$
– Max
Apr 18 at 11:52
|
show 1 more comment
$begingroup$
I tried to find the the precise definition of a nonlinear signal. However it is not easy. How can we define a nonlinear signal?
signal-analysis
New contributor
$endgroup$
I tried to find the the precise definition of a nonlinear signal. However it is not easy. How can we define a nonlinear signal?
signal-analysis
signal-analysis
New contributor
New contributor
New contributor
asked Apr 18 at 7:31
cabalcabal
41
41
New contributor
New contributor
2
$begingroup$
Do you really mean a nonlinear signal? Or maybe a nonlinear system?
$endgroup$
– Max
Apr 18 at 7:46
$begingroup$
I mean a nonlinear signal.
$endgroup$
– cabal
Apr 18 at 10:08
$begingroup$
@cabal: The term really doesn't make much sense. Can you provide a reference where it's being used or did you come up with it yourself?
$endgroup$
– Hilmar
Apr 18 at 10:46
$begingroup$
I found it in "Encyclopedia of Information Science and Technology". Here is the link to the definition: igi-global.com/dictionary/…
$endgroup$
– cabal
Apr 18 at 10:50
$begingroup$
Well, the definition is there. A signal, that comes out of a nonlinear system. Refer to Matt's answer.
$endgroup$
– Max
Apr 18 at 11:52
|
show 1 more comment
2
$begingroup$
Do you really mean a nonlinear signal? Or maybe a nonlinear system?
$endgroup$
– Max
Apr 18 at 7:46
$begingroup$
I mean a nonlinear signal.
$endgroup$
– cabal
Apr 18 at 10:08
$begingroup$
@cabal: The term really doesn't make much sense. Can you provide a reference where it's being used or did you come up with it yourself?
$endgroup$
– Hilmar
Apr 18 at 10:46
$begingroup$
I found it in "Encyclopedia of Information Science and Technology". Here is the link to the definition: igi-global.com/dictionary/…
$endgroup$
– cabal
Apr 18 at 10:50
$begingroup$
Well, the definition is there. A signal, that comes out of a nonlinear system. Refer to Matt's answer.
$endgroup$
– Max
Apr 18 at 11:52
2
2
$begingroup$
Do you really mean a nonlinear signal? Or maybe a nonlinear system?
$endgroup$
– Max
Apr 18 at 7:46
$begingroup$
Do you really mean a nonlinear signal? Or maybe a nonlinear system?
$endgroup$
– Max
Apr 18 at 7:46
$begingroup$
I mean a nonlinear signal.
$endgroup$
– cabal
Apr 18 at 10:08
$begingroup$
I mean a nonlinear signal.
$endgroup$
– cabal
Apr 18 at 10:08
$begingroup$
@cabal: The term really doesn't make much sense. Can you provide a reference where it's being used or did you come up with it yourself?
$endgroup$
– Hilmar
Apr 18 at 10:46
$begingroup$
@cabal: The term really doesn't make much sense. Can you provide a reference where it's being used or did you come up with it yourself?
$endgroup$
– Hilmar
Apr 18 at 10:46
$begingroup$
I found it in "Encyclopedia of Information Science and Technology". Here is the link to the definition: igi-global.com/dictionary/…
$endgroup$
– cabal
Apr 18 at 10:50
$begingroup$
I found it in "Encyclopedia of Information Science and Technology". Here is the link to the definition: igi-global.com/dictionary/…
$endgroup$
– cabal
Apr 18 at 10:50
$begingroup$
Well, the definition is there. A signal, that comes out of a nonlinear system. Refer to Matt's answer.
$endgroup$
– Max
Apr 18 at 11:52
$begingroup$
Well, the definition is there. A signal, that comes out of a nonlinear system. Refer to Matt's answer.
$endgroup$
– Max
Apr 18 at 11:52
|
show 1 more comment
3 Answers
3
active
oldest
votes
$begingroup$
In my opinion, the term nonlinear signal doesn't make much sense. If you refer to nonlinear signal processing then this is not about the processing of nonlinear signals, but about the nonlinear processing of signals, i.e., about the use of nonlinear systems.
A system $mathcalT$ is nonlinear if it doesn't obey the superposition principle. I.e., if $y_1(t)=mathcalTx_1(t)$ is the response to input $x_1(t)$, and $y_2(t)=mathcalTx_2(t)$ is the response to input $x_2(t)$ then
$$mathcalTbigalpha x_1(t)+beta x_2(t)big=alphamathcalTbigx_1(t)big+betamathcalTbigx_2(t)big$$
is generally not satisfied.
Well-known examples of such nonlinear systems are median filters and Volterra filters, but there are many trivial operations, such as taking the magnitude of a signal, which must be classified as nonlinear processing.
$endgroup$
add a comment |
$begingroup$
Per https://www.igi-global.com/dictionary/nonlinear-approach-brain-signal-modeling/36494 it's defined as
A nonlinear signal is generally defined as the signal generated by the
system that does not obey superposition and scaling properties.
You can certainly define it that way, but it seems like a useless definition since it doesn't reference any property of the signal itself.
Consider a case where you have a non-linear system followed by an linear "pass through" system. Per the definition, the output of the non-linear system would be a "non-linear signal" and the output of the pass-through would be a "linear" signal. Since the linear system is pass-through the input and output are the same, so now you have two signals that are identical but one of them is "non-linear" and the other one isn't. That really doesn't make any sense, so the definitions seem pointless and not useful for anything.
$endgroup$
add a comment |
$begingroup$
There are materials where the strain/stress relationship becomes nonlinear at high signal amplitude that are studied in nonlinear acoustics.
The same can be true in optics where high amplitude fields changes a linear propagation to a nonlinear one.
I believe action potentials in nerves are nonlinear.
The term “small signal” has been associated with linear propagating signals.
I can’t say I’ve seen the terms linear or nonlinear signals used.
$endgroup$
add a comment |
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3 Answers
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active
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3 Answers
3
active
oldest
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active
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active
oldest
votes
$begingroup$
In my opinion, the term nonlinear signal doesn't make much sense. If you refer to nonlinear signal processing then this is not about the processing of nonlinear signals, but about the nonlinear processing of signals, i.e., about the use of nonlinear systems.
A system $mathcalT$ is nonlinear if it doesn't obey the superposition principle. I.e., if $y_1(t)=mathcalTx_1(t)$ is the response to input $x_1(t)$, and $y_2(t)=mathcalTx_2(t)$ is the response to input $x_2(t)$ then
$$mathcalTbigalpha x_1(t)+beta x_2(t)big=alphamathcalTbigx_1(t)big+betamathcalTbigx_2(t)big$$
is generally not satisfied.
Well-known examples of such nonlinear systems are median filters and Volterra filters, but there are many trivial operations, such as taking the magnitude of a signal, which must be classified as nonlinear processing.
$endgroup$
add a comment |
$begingroup$
In my opinion, the term nonlinear signal doesn't make much sense. If you refer to nonlinear signal processing then this is not about the processing of nonlinear signals, but about the nonlinear processing of signals, i.e., about the use of nonlinear systems.
A system $mathcalT$ is nonlinear if it doesn't obey the superposition principle. I.e., if $y_1(t)=mathcalTx_1(t)$ is the response to input $x_1(t)$, and $y_2(t)=mathcalTx_2(t)$ is the response to input $x_2(t)$ then
$$mathcalTbigalpha x_1(t)+beta x_2(t)big=alphamathcalTbigx_1(t)big+betamathcalTbigx_2(t)big$$
is generally not satisfied.
Well-known examples of such nonlinear systems are median filters and Volterra filters, but there are many trivial operations, such as taking the magnitude of a signal, which must be classified as nonlinear processing.
$endgroup$
add a comment |
$begingroup$
In my opinion, the term nonlinear signal doesn't make much sense. If you refer to nonlinear signal processing then this is not about the processing of nonlinear signals, but about the nonlinear processing of signals, i.e., about the use of nonlinear systems.
A system $mathcalT$ is nonlinear if it doesn't obey the superposition principle. I.e., if $y_1(t)=mathcalTx_1(t)$ is the response to input $x_1(t)$, and $y_2(t)=mathcalTx_2(t)$ is the response to input $x_2(t)$ then
$$mathcalTbigalpha x_1(t)+beta x_2(t)big=alphamathcalTbigx_1(t)big+betamathcalTbigx_2(t)big$$
is generally not satisfied.
Well-known examples of such nonlinear systems are median filters and Volterra filters, but there are many trivial operations, such as taking the magnitude of a signal, which must be classified as nonlinear processing.
$endgroup$
In my opinion, the term nonlinear signal doesn't make much sense. If you refer to nonlinear signal processing then this is not about the processing of nonlinear signals, but about the nonlinear processing of signals, i.e., about the use of nonlinear systems.
A system $mathcalT$ is nonlinear if it doesn't obey the superposition principle. I.e., if $y_1(t)=mathcalTx_1(t)$ is the response to input $x_1(t)$, and $y_2(t)=mathcalTx_2(t)$ is the response to input $x_2(t)$ then
$$mathcalTbigalpha x_1(t)+beta x_2(t)big=alphamathcalTbigx_1(t)big+betamathcalTbigx_2(t)big$$
is generally not satisfied.
Well-known examples of such nonlinear systems are median filters and Volterra filters, but there are many trivial operations, such as taking the magnitude of a signal, which must be classified as nonlinear processing.
answered Apr 18 at 9:41
Matt L.Matt L.
51.6k23994
51.6k23994
add a comment |
add a comment |
$begingroup$
Per https://www.igi-global.com/dictionary/nonlinear-approach-brain-signal-modeling/36494 it's defined as
A nonlinear signal is generally defined as the signal generated by the
system that does not obey superposition and scaling properties.
You can certainly define it that way, but it seems like a useless definition since it doesn't reference any property of the signal itself.
Consider a case where you have a non-linear system followed by an linear "pass through" system. Per the definition, the output of the non-linear system would be a "non-linear signal" and the output of the pass-through would be a "linear" signal. Since the linear system is pass-through the input and output are the same, so now you have two signals that are identical but one of them is "non-linear" and the other one isn't. That really doesn't make any sense, so the definitions seem pointless and not useful for anything.
$endgroup$
add a comment |
$begingroup$
Per https://www.igi-global.com/dictionary/nonlinear-approach-brain-signal-modeling/36494 it's defined as
A nonlinear signal is generally defined as the signal generated by the
system that does not obey superposition and scaling properties.
You can certainly define it that way, but it seems like a useless definition since it doesn't reference any property of the signal itself.
Consider a case where you have a non-linear system followed by an linear "pass through" system. Per the definition, the output of the non-linear system would be a "non-linear signal" and the output of the pass-through would be a "linear" signal. Since the linear system is pass-through the input and output are the same, so now you have two signals that are identical but one of them is "non-linear" and the other one isn't. That really doesn't make any sense, so the definitions seem pointless and not useful for anything.
$endgroup$
add a comment |
$begingroup$
Per https://www.igi-global.com/dictionary/nonlinear-approach-brain-signal-modeling/36494 it's defined as
A nonlinear signal is generally defined as the signal generated by the
system that does not obey superposition and scaling properties.
You can certainly define it that way, but it seems like a useless definition since it doesn't reference any property of the signal itself.
Consider a case where you have a non-linear system followed by an linear "pass through" system. Per the definition, the output of the non-linear system would be a "non-linear signal" and the output of the pass-through would be a "linear" signal. Since the linear system is pass-through the input and output are the same, so now you have two signals that are identical but one of them is "non-linear" and the other one isn't. That really doesn't make any sense, so the definitions seem pointless and not useful for anything.
$endgroup$
Per https://www.igi-global.com/dictionary/nonlinear-approach-brain-signal-modeling/36494 it's defined as
A nonlinear signal is generally defined as the signal generated by the
system that does not obey superposition and scaling properties.
You can certainly define it that way, but it seems like a useless definition since it doesn't reference any property of the signal itself.
Consider a case where you have a non-linear system followed by an linear "pass through" system. Per the definition, the output of the non-linear system would be a "non-linear signal" and the output of the pass-through would be a "linear" signal. Since the linear system is pass-through the input and output are the same, so now you have two signals that are identical but one of them is "non-linear" and the other one isn't. That really doesn't make any sense, so the definitions seem pointless and not useful for anything.
answered Apr 18 at 13:11
HilmarHilmar
10.6k1218
10.6k1218
add a comment |
add a comment |
$begingroup$
There are materials where the strain/stress relationship becomes nonlinear at high signal amplitude that are studied in nonlinear acoustics.
The same can be true in optics where high amplitude fields changes a linear propagation to a nonlinear one.
I believe action potentials in nerves are nonlinear.
The term “small signal” has been associated with linear propagating signals.
I can’t say I’ve seen the terms linear or nonlinear signals used.
$endgroup$
add a comment |
$begingroup$
There are materials where the strain/stress relationship becomes nonlinear at high signal amplitude that are studied in nonlinear acoustics.
The same can be true in optics where high amplitude fields changes a linear propagation to a nonlinear one.
I believe action potentials in nerves are nonlinear.
The term “small signal” has been associated with linear propagating signals.
I can’t say I’ve seen the terms linear or nonlinear signals used.
$endgroup$
add a comment |
$begingroup$
There are materials where the strain/stress relationship becomes nonlinear at high signal amplitude that are studied in nonlinear acoustics.
The same can be true in optics where high amplitude fields changes a linear propagation to a nonlinear one.
I believe action potentials in nerves are nonlinear.
The term “small signal” has been associated with linear propagating signals.
I can’t say I’ve seen the terms linear or nonlinear signals used.
$endgroup$
There are materials where the strain/stress relationship becomes nonlinear at high signal amplitude that are studied in nonlinear acoustics.
The same can be true in optics where high amplitude fields changes a linear propagation to a nonlinear one.
I believe action potentials in nerves are nonlinear.
The term “small signal” has been associated with linear propagating signals.
I can’t say I’ve seen the terms linear or nonlinear signals used.
answered Apr 18 at 12:41
Stanley PawlukiewiczStanley Pawlukiewicz
6,4642523
6,4642523
add a comment |
add a comment |
cabal is a new contributor. Be nice, and check out our Code of Conduct.
cabal is a new contributor. Be nice, and check out our Code of Conduct.
cabal is a new contributor. Be nice, and check out our Code of Conduct.
cabal is a new contributor. Be nice, and check out our Code of Conduct.
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2
$begingroup$
Do you really mean a nonlinear signal? Or maybe a nonlinear system?
$endgroup$
– Max
Apr 18 at 7:46
$begingroup$
I mean a nonlinear signal.
$endgroup$
– cabal
Apr 18 at 10:08
$begingroup$
@cabal: The term really doesn't make much sense. Can you provide a reference where it's being used or did you come up with it yourself?
$endgroup$
– Hilmar
Apr 18 at 10:46
$begingroup$
I found it in "Encyclopedia of Information Science and Technology". Here is the link to the definition: igi-global.com/dictionary/…
$endgroup$
– cabal
Apr 18 at 10:50
$begingroup$
Well, the definition is there. A signal, that comes out of a nonlinear system. Refer to Matt's answer.
$endgroup$
– Max
Apr 18 at 11:52