Is a System Causal if the Output Anticipates the Input?

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In summary, a causal system means that the system is not anticipatory. In your example, y[n] = sin[n], the output y[N] at a given time N does NOT depend on any information after "time" N - so the system is causal.
  • #1
johnstamos
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Hey guys, having a little trouble understanding whether or not a system is causal or not. I d'nt think this classifies as homework; at least I hope not.

Basically I'm confused as to how you would go about determining whether or not a system is causal.

For example, say any function x[n] = u[n];

So basically the signal is only active for n>=0;

y[n] = sin[n];

So you have an output for n<=0 when there is no signal propogating into the system. Thus I would assume that this system is non-causal, because the output is somehow anticipatory.

However, what if the output y[n] actually does depend on inputs of 0. So y[n] for n<=0 actually does result from x[n] = 0, wouldn't that make it causal then?

Not sure if this makes any sense whatsoever, hopefully someone can share some insight on this topic.
 
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  • #2
Hey,

I don't really understand your example. LKike you said a causal system means that the system is NOT anticipatory. This means that for a system y[n] = F[x(n)], y[N] does not depend on any values of x for values of n>N.

in your example y[n] = sin[n], the output y[N] at a given time N does NOT depend on any information after "time" N - so the system is causal.

One easy way to check is to think: can you determine the output y[N]with only knowing x[n] for n<=N. If you can, your system is causal.

It may help to see an example of a non-causal function:

y[n] = x[n] + x[n+1]

As you can see here, you MUST know the value of x at N+1 in order to know the value of the output y[N].
 
  • #3
yeah not the best english student!

basically if the system has input u[n] and output cos[n], then is that system causal?

Because the output has values for n<=0 whereas the input only has values for n>=0.

Therefore the output is anticipating the input? That's bascially my question.
 

1. What is a causal system?

A causal system is a system in which a change in one variable leads to a change in another variable. In other words, there is a cause-and-effect relationship between the variables.

2. How do scientists determine causal systems?

Scientists determine causal systems through experiments, statistical analysis, and observation. They manipulate one variable and observe the effect on another variable to establish a causal relationship.

3. What is the importance of determining causal systems?

Determining causal systems is important because it allows us to understand the relationship between variables and make predictions about how changes in one variable will affect another. This knowledge is crucial in fields such as medicine, economics, and social sciences.

4. Can correlation imply causation?

No, correlation does not necessarily imply causation. Just because two variables are correlated, it does not mean that one causes the other. There could be other factors at play that are causing the observed relationship.

5. How do scientists account for confounding variables when determining causal systems?

Scientists account for confounding variables by controlling them in experiments, using statistical techniques to isolate their effects, or by conducting multiple studies to rule out alternative explanations. It is important to identify and control for confounding variables to establish a strong causal relationship between the variables of interest.

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