Does a causal system have to be non-recursive?

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SUMMARY

A causal discrete system is defined by its output at time T depending solely on inputs from times t ≤ T, ensuring that it operates without knowledge of future inputs. Recursiveness, which allows outputs to depend on previous outputs, does not affect the causality of the system. While recursiveness is not a requirement for a causal system, it can enhance filter design by enabling the output to incorporate a broader range of past inputs. An example of this is the digital exponential smoothing filter, which averages current and previous inputs.

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Bipolarity
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I have been trying to search for a clear definition of "discrete causal systems". The thing I want to know, which I've not been able to find, is whether non-recursiveness of the difference equation is part of the requirement for a causal discrete system?

Thanks!

BiP
 
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A causal system is just one where the output at time ##T## only depends on the input at times ##t \le T##. In other words, the filter doesn't know anything about the future. That is a requirement for any filter that operates in real time (unless you want to change the laws of physics!) . If you are filtering data that has been acquired in the past, the filter doesn't have to be causal.

Recursiveness is irrelevant. That just says the output at time ##T## also depends on the output at times ##t \le T##, but those outputs ultimately depend on the inputs.

Recursiveness is useful in practice because you can design a filter that does a finite number of "operations" (either analog or digital) but the output depends on all the input from times ##-\infty < t \le T##. A simple example would be an digital "exponential smoothing" filter where the output at time ##T## is a weighted average of the input at time ##T##, and the output at the previous time ##T-\delta t##.
 
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