Causal Systems: Understanding the Basics

In summary, the system defined by y(t) = x(t-1) is causal although x(t-1) is something else than x(t).
  • #1
Tom McCurdy
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We have been going over causal systems and I am still having trouble determining what defines a system to be causal.

I was told that if the input is anything besides x(a*t) where a=1 then the system is non causal. I can kind of see this, but it is still a bit blurry for me. I also was wondering if that would still apply if you removed t directly from the input equation...

say like if you had [tex] y(t) = \int_{-\infty}^{t}x(5{\tau}) d\tau [/tex]

then is this automatically not causal because of the the 5 coefficient on the inside of x()
 
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  • #2
Tom McCurdy said:
I was told that if the input is anything besides x(a*t) where a=1 then the system is non causal.

That's not true.

The system defined by [tex]y(t) = x(t-1)[/tex] is causal although [tex]x(t-1)[/tex] is something else than [tex]x(t)[/tex].

The general definition for a causal system (linear or non-linear, time-invariant or time-variant) is:

Given 2 input signals [tex]x_1(t)[/tex] and [tex]x_2(t)[/tex] such that [tex]x_1(t) = x_2(t)[/tex] for any [tex]t < t_0[/tex], the system is causal if the output signals [tex]y_1(t) = y_2(t)[/tex] for any [tex]t < t_0[/tex]

If the system is linear then if we apply a signal [tex]x(t) = x_1(t) - x_2(t)[/tex] the output should be [tex]y(t) = y_1(t) - y_2(t)[/tex], so the condition for the system to be causal (in the case of linear systems) reduces to:

if [tex]x(t) = 0[/tex] for [tex]t<t_0[/tex] then [tex]y(t) = 0[/tex] for [tex]t<t_0[/tex]

If the system is linear and time invariant, the condition for causality reduces to:

[tex]h(t)=0[/tex] for [tex]t<0[/tex]

So depending on the kind of system and your known data you should check one of these conditions.

In the case of [tex] y(t) = \int_{-\infty}^{t}x(5{\tau}) d\tau [/tex] I know that it's linear because it's defined by an integral which is a linear operation so I will check the second condition.
I pick an instant [tex]t_0[/tex] at which the output will be [tex] y(t_0) = \int_{-\infty}^{t_0}x(5{\tau}) d\tau [/tex]

So we see that the output depends on values of [tex]x(t)[/tex] till [tex]5t_0[/tex] but
we know that [tex]x(t) = 0[/tex] only for [tex]t<t_0[/tex] and thus the output will not be 0 for any [tex]t<t_0[/tex] which means that the system is not causal.
 
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  • #3
i sort of like the Wikipedia definition of causal system (i had a hand in it before they kicked me out of Wikipedia):

A causal system (also known as a ... nonanticipative system) is a system where the output [itex]y(t)[/itex] at some specific instant [itex]t_{0}[/itex] only depends on the input [itex]x(t)[/itex] for values of [itex]t[/itex] less than or equal to [itex]t_{0}[/itex] . Therefore these kinds of systems have outputs and internal states that depends only on the current and previous input values.

The idea that the output of a function at any time depends only on past and present values of input is defined by the property commonly referred to as causality.
antonantal said:
If the system is linear and time invariant, the condition for causality reduces to:

[tex]h(t)=0[/tex] for [tex]t<t_0[/tex]

i think you can conclude that for an LTI system, causality is equivalent to the impulse response h(t) being zero for all t < 0. t0 is not a parameter of the impulse response. the impulse response is the LTI to a unit impulse applied at t=0.
 
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  • #4
rbj said:
i think you can conclude that for an LTI system, causality is equivalent to the impulse response h(t) being zero for all t < 0. t0 is not a parameter of the impulse response. the impulse response is the LTI to a unit impulse applied at t=0.

You're right of course. I just copied the latex expression above it and forgot to replace t0 with 0 as well. I'll edit it now. Thanks!
 

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