Does a causal system have to be non-recursive?

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A causal discrete system requires that the output at time T depends only on inputs from times t ≤ T, ensuring it does not anticipate future inputs. Non-recursiveness is not a requirement for a causal system; it merely indicates that the output may also depend on previous outputs. While recursiveness can be beneficial for practical filter design, it does not affect the fundamental causal nature of the system. An example of a recursive filter is digital exponential smoothing, which averages current and past inputs. Understanding these distinctions clarifies the nature of causal systems in signal processing.
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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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