Electrical Engineering (EE)  >  Digital Signal Processing  >  Causal, Non Causal & Anti Causal Systems

Causal, Non Causal & Anti Causal Systems Notes | Study Digital Signal Processing - Electrical Engineering (EE)

Document Description: Causal, Non Causal & Anti Causal Systems for Electrical Engineering (EE) 2022 is part of Digital Signal Processing preparation. The notes and questions for Causal, Non Causal & Anti Causal Systems have been prepared according to the Electrical Engineering (EE) exam syllabus. Information about Causal, Non Causal & Anti Causal Systems covers topics like and Causal, Non Causal & Anti Causal Systems Example, for Electrical Engineering (EE) 2022 Exam. Find important definitions, questions, notes, meanings, examples, exercises and tests below for Causal, Non Causal & Anti Causal Systems.

Introduction of Causal, Non Causal & Anti Causal Systems in English is available as part of our Digital Signal Processing for Electrical Engineering (EE) & Causal, Non Causal & Anti Causal Systems in Hindi for Digital Signal Processing course. Download more important topics related with notes, lectures and mock test series for Electrical Engineering (EE) Exam by signing up for free. Electrical Engineering (EE): Causal, Non Causal & Anti Causal Systems Notes | Study Digital Signal Processing - Electrical Engineering (EE)
1 Crore+ students have signed up on EduRev. Have you?

Previously, we saw that the system needs to be independent from the future and past values to become static. In this case, the condition is almost same with little modification. Here, for the system to be causal, it should be independent from the future values only. That means past dependency will cause no problem for the system from becoming causal.

Causal systems are practically or physically realizable system. Let us consider some examples to understand this much better.

Examples

Let us consider the following signals.

a) y(t) = x(t)

Here, the signal is only dependent on the present values of x. For example if we substitute t = 3, the result will show for that instant of time only. Therefore, as it has no dependence on future value, we can call it a Causal system.

b) y(t) = x(t−1)

Here, the system depends on past values. For instance if we substitute t = 3, the expression will reduce to x(2), which is a past value against our input. At no instance, it depends upon future values. Therefore, this system is also a causal system.

c) y(t) = x(t) + x(t+1)

In this case, the system has two parts. The part x(t), as we have discussed earlier, depends only upon the present values. So, there is no issue with it. However, if we take the case of x(t+1), it clearly depends on the future values because if we put t = 1, the expression will reduce to x(2) which is future value. Therefore, it is not causal.

A non-causal system is just opposite to that of causal system. If a system depends upon the future values of the input at any instant of the time then the system is said to be non-causal system.

Examples

Let us take some examples and try to understand this in a better way.

a) y(t) = x(t+1)

We have already discussed this system in causal system too. For any input, it will reduce the system to its future value. For instance, if we put t = 2, it will reduce to x(3), which is a future value. Therefore, the system is Non-Causal.

b) y(t) = x(t) + x(t+2)

In this case, x(t) is purely a present value dependent function. We have already discussed that x(t+2) function is future dependent because for t = 3 it will give values for x(5). Therefore, it is Non-causal.

c) y(t) = x(t−1) + x(t)

In this system, it depends upon the present and past values of the given input. Whatever values we substitute, it will never show any future dependency. Clearly, it is not a non-causal system; rather it is a Causal system.

An anti-causal system is just a little bit modified version of a non-causal system. The system depends upon the future values of the input only. It has no dependency either on present or on the past values.

Examples

Find out whether the following systems are anti-causal.

a) y(t) = x(t) + x(t−1)

The system has two sub-functions. One sub function x(t+1) depends on the future value of the input but another sub-function x(t) depends only on the present. As the system is dependent on the present value also in addition to future value, this system is not anti-causal.

b) y(t) = x(t+3)

If we analyze the above system, we can see that the system depends only on the future values of the system i.e. if we put t = 0, it will reduce to x(3), which is a future value. This system is a perfect example of anti-causal system.

The document Causal, Non Causal & Anti Causal Systems Notes | Study Digital Signal Processing - Electrical Engineering (EE) is a part of the Electrical Engineering (EE) Course Digital Signal Processing.
All you need of Electrical Engineering (EE) at this link: Electrical Engineering (EE)

Related Searches

Non Causal & Anti Causal Systems Notes | Study Digital Signal Processing - Electrical Engineering (EE)

,

Important questions

,

Non Causal & Anti Causal Systems Notes | Study Digital Signal Processing - Electrical Engineering (EE)

,

pdf

,

Exam

,

Causal

,

Causal

,

Previous Year Questions with Solutions

,

mock tests for examination

,

ppt

,

MCQs

,

Viva Questions

,

Non Causal & Anti Causal Systems Notes | Study Digital Signal Processing - Electrical Engineering (EE)

,

Causal

,

video lectures

,

Extra Questions

,

Sample Paper

,

Semester Notes

,

past year papers

,

Free

,

practice quizzes

,

Objective type Questions

,

shortcuts and tricks

,

Summary

,

study material

;