Determine whether the system is linear?












3















$T(x[n]) = ax[n] + b$




$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+ alpha_{2}ax_{2} [n] +b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



therefore they are not equal so the system is non-linear?



or would it be something like this:



$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+alpha_{1}b + alpha_{2}ax_{2} [n] + alpha_{2}b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



and therefore they are equal so the system is linear?










share|improve this question




















  • 1




    This is an example of incrementally linear system.
    – Fat32
    Nov 26 '18 at 20:04
















3















$T(x[n]) = ax[n] + b$




$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+ alpha_{2}ax_{2} [n] +b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



therefore they are not equal so the system is non-linear?



or would it be something like this:



$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+alpha_{1}b + alpha_{2}ax_{2} [n] + alpha_{2}b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



and therefore they are equal so the system is linear?










share|improve this question




















  • 1




    This is an example of incrementally linear system.
    – Fat32
    Nov 26 '18 at 20:04














3












3








3


1






$T(x[n]) = ax[n] + b$




$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+ alpha_{2}ax_{2} [n] +b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



therefore they are not equal so the system is non-linear?



or would it be something like this:



$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+alpha_{1}b + alpha_{2}ax_{2} [n] + alpha_{2}b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



and therefore they are equal so the system is linear?










share|improve this question
















$T(x[n]) = ax[n] + b$




$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+ alpha_{2}ax_{2} [n] +b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



therefore they are not equal so the system is non-linear?



or would it be something like this:



$ T(alpha_{1}x_{1}[n] + alpha_{2}x_{2}[n]) = alpha_{1}ax_{1}[n]+alpha_{1}b + alpha_{2}ax_{2} [n] + alpha_{2}b $



$ alpha_{1}T(x_{1}[n] ) + alpha_{2}T(x_{2}[n]) = alpha_{1}(ax[n]+b) + alpha_{2}(ax_{2} [n] +b) $



and therefore they are equal so the system is linear?







homework system-identification






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 26 '18 at 19:04

























asked Nov 26 '18 at 18:49









roffensive

454




454








  • 1




    This is an example of incrementally linear system.
    – Fat32
    Nov 26 '18 at 20:04














  • 1




    This is an example of incrementally linear system.
    – Fat32
    Nov 26 '18 at 20:04








1




1




This is an example of incrementally linear system.
– Fat32
Nov 26 '18 at 20:04




This is an example of incrementally linear system.
– Fat32
Nov 26 '18 at 20:04










2 Answers
2






active

oldest

votes


















3














I don't really understand the motivation behind the second group of equations, or why $b$ gets multiplied by $alpha_i$.



Here, you are using the generic version of the linearity test, which is good, but can raise some doubts, as apparent from your question. You can, in complement, use other simpler tests, that can show that the system is not linear, as a double check. Those are counter-examples. For instance:




  • is the output of the zero signal zero? For a linear system , $T(vec{0})=0$.

  • is a single output with a zero coefficient zero? This tests if $T(0.vec{x})=0.T(vec{x}) = 0$

  • is a single output linear? This tests if $T(alpha.vec{x})=alpha.T(vec{x})$

  • is a simple addition linear? This tests if $T(vec{x}+vec{y})=T(vec{x})+T(vec{y})$


Those, if not passed, prove that the system is non-linear. And instead of using the generic version, they can show to your (clever) professor that you have some intuition about what is going on, and the risk of errors is reduced. I personally appreciate a lot when students use minimal arguments: they go straight to the point, spend less time on such questions, to focus on more involved ones.



Of course, if the system is linear, more is required.



Here, your system is non-linear... unless $b=0$.






share|improve this answer































    2














    Though Laurent gave the standard answer of the linear system. We shall also note that this is an incrementally linear system and it could be made linear by the following argumentation:



    Let the first system (your system) be given by the following I/O relationship:



    $$ y[n] = mathcal{T}{ x[n] } = a~x[n] + b $$ where $a$ and $b$ are constants.



    This system, $mathcal{T}$, is clearly not linear. However if you define the following second system, $mathcal{S}$, as:



    $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a }. $$



    Then $mathcal{S}$ will be a linear system as easily demonstrated :



    $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a } = ( x[n] - b/a) cdot a + b = a~x[n]. $$ Hence effectively the second system is



    $$ y[n] = mathcal{S}{ x[n] } = a ~x[n] $$ a linear one.



    So by this method, you can convert any incrementally linear system to an equivalent linear one. Most typically $b$ can be seen as a bias term that prevented the former system to be linear, and when properly removed the linearity is reclaimed...



    Of course, strictly speaking, $S$ is not the same system with $T$, it's another system.






    share|improve this answer





















    • Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
      – Laurent Duval
      Nov 26 '18 at 22:21








    • 1




      Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
      – Fat32
      Nov 26 '18 at 22:49








    • 2




      That's ah, fine
      – Laurent Duval
      Nov 26 '18 at 22:53











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    2 Answers
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    2 Answers
    2






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    active

    oldest

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    active

    oldest

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    3














    I don't really understand the motivation behind the second group of equations, or why $b$ gets multiplied by $alpha_i$.



    Here, you are using the generic version of the linearity test, which is good, but can raise some doubts, as apparent from your question. You can, in complement, use other simpler tests, that can show that the system is not linear, as a double check. Those are counter-examples. For instance:




    • is the output of the zero signal zero? For a linear system , $T(vec{0})=0$.

    • is a single output with a zero coefficient zero? This tests if $T(0.vec{x})=0.T(vec{x}) = 0$

    • is a single output linear? This tests if $T(alpha.vec{x})=alpha.T(vec{x})$

    • is a simple addition linear? This tests if $T(vec{x}+vec{y})=T(vec{x})+T(vec{y})$


    Those, if not passed, prove that the system is non-linear. And instead of using the generic version, they can show to your (clever) professor that you have some intuition about what is going on, and the risk of errors is reduced. I personally appreciate a lot when students use minimal arguments: they go straight to the point, spend less time on such questions, to focus on more involved ones.



    Of course, if the system is linear, more is required.



    Here, your system is non-linear... unless $b=0$.






    share|improve this answer




























      3














      I don't really understand the motivation behind the second group of equations, or why $b$ gets multiplied by $alpha_i$.



      Here, you are using the generic version of the linearity test, which is good, but can raise some doubts, as apparent from your question. You can, in complement, use other simpler tests, that can show that the system is not linear, as a double check. Those are counter-examples. For instance:




      • is the output of the zero signal zero? For a linear system , $T(vec{0})=0$.

      • is a single output with a zero coefficient zero? This tests if $T(0.vec{x})=0.T(vec{x}) = 0$

      • is a single output linear? This tests if $T(alpha.vec{x})=alpha.T(vec{x})$

      • is a simple addition linear? This tests if $T(vec{x}+vec{y})=T(vec{x})+T(vec{y})$


      Those, if not passed, prove that the system is non-linear. And instead of using the generic version, they can show to your (clever) professor that you have some intuition about what is going on, and the risk of errors is reduced. I personally appreciate a lot when students use minimal arguments: they go straight to the point, spend less time on such questions, to focus on more involved ones.



      Of course, if the system is linear, more is required.



      Here, your system is non-linear... unless $b=0$.






      share|improve this answer


























        3












        3








        3






        I don't really understand the motivation behind the second group of equations, or why $b$ gets multiplied by $alpha_i$.



        Here, you are using the generic version of the linearity test, which is good, but can raise some doubts, as apparent from your question. You can, in complement, use other simpler tests, that can show that the system is not linear, as a double check. Those are counter-examples. For instance:




        • is the output of the zero signal zero? For a linear system , $T(vec{0})=0$.

        • is a single output with a zero coefficient zero? This tests if $T(0.vec{x})=0.T(vec{x}) = 0$

        • is a single output linear? This tests if $T(alpha.vec{x})=alpha.T(vec{x})$

        • is a simple addition linear? This tests if $T(vec{x}+vec{y})=T(vec{x})+T(vec{y})$


        Those, if not passed, prove that the system is non-linear. And instead of using the generic version, they can show to your (clever) professor that you have some intuition about what is going on, and the risk of errors is reduced. I personally appreciate a lot when students use minimal arguments: they go straight to the point, spend less time on such questions, to focus on more involved ones.



        Of course, if the system is linear, more is required.



        Here, your system is non-linear... unless $b=0$.






        share|improve this answer














        I don't really understand the motivation behind the second group of equations, or why $b$ gets multiplied by $alpha_i$.



        Here, you are using the generic version of the linearity test, which is good, but can raise some doubts, as apparent from your question. You can, in complement, use other simpler tests, that can show that the system is not linear, as a double check. Those are counter-examples. For instance:




        • is the output of the zero signal zero? For a linear system , $T(vec{0})=0$.

        • is a single output with a zero coefficient zero? This tests if $T(0.vec{x})=0.T(vec{x}) = 0$

        • is a single output linear? This tests if $T(alpha.vec{x})=alpha.T(vec{x})$

        • is a simple addition linear? This tests if $T(vec{x}+vec{y})=T(vec{x})+T(vec{y})$


        Those, if not passed, prove that the system is non-linear. And instead of using the generic version, they can show to your (clever) professor that you have some intuition about what is going on, and the risk of errors is reduced. I personally appreciate a lot when students use minimal arguments: they go straight to the point, spend less time on such questions, to focus on more involved ones.



        Of course, if the system is linear, more is required.



        Here, your system is non-linear... unless $b=0$.







        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 26 '18 at 22:57

























        answered Nov 26 '18 at 19:11









        Laurent Duval

        16.4k32059




        16.4k32059























            2














            Though Laurent gave the standard answer of the linear system. We shall also note that this is an incrementally linear system and it could be made linear by the following argumentation:



            Let the first system (your system) be given by the following I/O relationship:



            $$ y[n] = mathcal{T}{ x[n] } = a~x[n] + b $$ where $a$ and $b$ are constants.



            This system, $mathcal{T}$, is clearly not linear. However if you define the following second system, $mathcal{S}$, as:



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a }. $$



            Then $mathcal{S}$ will be a linear system as easily demonstrated :



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a } = ( x[n] - b/a) cdot a + b = a~x[n]. $$ Hence effectively the second system is



            $$ y[n] = mathcal{S}{ x[n] } = a ~x[n] $$ a linear one.



            So by this method, you can convert any incrementally linear system to an equivalent linear one. Most typically $b$ can be seen as a bias term that prevented the former system to be linear, and when properly removed the linearity is reclaimed...



            Of course, strictly speaking, $S$ is not the same system with $T$, it's another system.






            share|improve this answer





















            • Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
              – Laurent Duval
              Nov 26 '18 at 22:21








            • 1




              Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
              – Fat32
              Nov 26 '18 at 22:49








            • 2




              That's ah, fine
              – Laurent Duval
              Nov 26 '18 at 22:53
















            2














            Though Laurent gave the standard answer of the linear system. We shall also note that this is an incrementally linear system and it could be made linear by the following argumentation:



            Let the first system (your system) be given by the following I/O relationship:



            $$ y[n] = mathcal{T}{ x[n] } = a~x[n] + b $$ where $a$ and $b$ are constants.



            This system, $mathcal{T}$, is clearly not linear. However if you define the following second system, $mathcal{S}$, as:



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a }. $$



            Then $mathcal{S}$ will be a linear system as easily demonstrated :



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a } = ( x[n] - b/a) cdot a + b = a~x[n]. $$ Hence effectively the second system is



            $$ y[n] = mathcal{S}{ x[n] } = a ~x[n] $$ a linear one.



            So by this method, you can convert any incrementally linear system to an equivalent linear one. Most typically $b$ can be seen as a bias term that prevented the former system to be linear, and when properly removed the linearity is reclaimed...



            Of course, strictly speaking, $S$ is not the same system with $T$, it's another system.






            share|improve this answer





















            • Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
              – Laurent Duval
              Nov 26 '18 at 22:21








            • 1




              Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
              – Fat32
              Nov 26 '18 at 22:49








            • 2




              That's ah, fine
              – Laurent Duval
              Nov 26 '18 at 22:53














            2












            2








            2






            Though Laurent gave the standard answer of the linear system. We shall also note that this is an incrementally linear system and it could be made linear by the following argumentation:



            Let the first system (your system) be given by the following I/O relationship:



            $$ y[n] = mathcal{T}{ x[n] } = a~x[n] + b $$ where $a$ and $b$ are constants.



            This system, $mathcal{T}$, is clearly not linear. However if you define the following second system, $mathcal{S}$, as:



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a }. $$



            Then $mathcal{S}$ will be a linear system as easily demonstrated :



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a } = ( x[n] - b/a) cdot a + b = a~x[n]. $$ Hence effectively the second system is



            $$ y[n] = mathcal{S}{ x[n] } = a ~x[n] $$ a linear one.



            So by this method, you can convert any incrementally linear system to an equivalent linear one. Most typically $b$ can be seen as a bias term that prevented the former system to be linear, and when properly removed the linearity is reclaimed...



            Of course, strictly speaking, $S$ is not the same system with $T$, it's another system.






            share|improve this answer












            Though Laurent gave the standard answer of the linear system. We shall also note that this is an incrementally linear system and it could be made linear by the following argumentation:



            Let the first system (your system) be given by the following I/O relationship:



            $$ y[n] = mathcal{T}{ x[n] } = a~x[n] + b $$ where $a$ and $b$ are constants.



            This system, $mathcal{T}$, is clearly not linear. However if you define the following second system, $mathcal{S}$, as:



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a }. $$



            Then $mathcal{S}$ will be a linear system as easily demonstrated :



            $$ y[n] = mathcal{S}{ x[n] } = mathcal{T}{ x[n] - b/a } = ( x[n] - b/a) cdot a + b = a~x[n]. $$ Hence effectively the second system is



            $$ y[n] = mathcal{S}{ x[n] } = a ~x[n] $$ a linear one.



            So by this method, you can convert any incrementally linear system to an equivalent linear one. Most typically $b$ can be seen as a bias term that prevented the former system to be linear, and when properly removed the linearity is reclaimed...



            Of course, strictly speaking, $S$ is not the same system with $T$, it's another system.







            share|improve this answer












            share|improve this answer



            share|improve this answer










            answered Nov 26 '18 at 20:15









            Fat32

            14.3k31129




            14.3k31129












            • Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
              – Laurent Duval
              Nov 26 '18 at 22:21








            • 1




              Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
              – Fat32
              Nov 26 '18 at 22:49








            • 2




              That's ah, fine
              – Laurent Duval
              Nov 26 '18 at 22:53


















            • Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
              – Laurent Duval
              Nov 26 '18 at 22:21








            • 1




              Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
              – Fat32
              Nov 26 '18 at 22:49








            • 2




              That's ah, fine
              – Laurent Duval
              Nov 26 '18 at 22:53
















            Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
            – Laurent Duval
            Nov 26 '18 at 22:21






            Aren't you trying to prove that a linear system is an affine one without an offet, somehow? :) How would you do with polynomial versions? Horner's rule?
            – Laurent Duval
            Nov 26 '18 at 22:21






            1




            1




            Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
            – Fat32
            Nov 26 '18 at 22:49






            Or probably I'm trying to avoid the term affine ;-) @LaurentDuval
            – Fat32
            Nov 26 '18 at 22:49






            2




            2




            That's ah, fine
            – Laurent Duval
            Nov 26 '18 at 22:53




            That's ah, fine
            – Laurent Duval
            Nov 26 '18 at 22:53


















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