Linearity, Time Invariance, Causality, ETC.

Click For Summary
SUMMARY

The system defined by the equation y(t) = 2x(t) + 3 is linear, time-invariant, causal, but not memoryless. The linearity is confirmed through the tests of homogeneity and additivity, which are essential in signal processing. The confusion arises from the differing definitions of linearity in algebra versus signal processing. The system does not satisfy the memoryless condition as it produces an output dependent on the input at the same time, but also includes a constant term.

PREREQUISITES
  • Understanding of signal processing concepts such as linearity, time invariance, causality, and memorylessness.
  • Familiarity with mathematical definitions of homogeneity and additivity.
  • Knowledge of polynomial algebra and its differences from signal processing definitions.
  • Basic grasp of input/output relationships in systems.
NEXT STEPS
  • Study the principles of linearity in signal processing, focusing on homogeneity and additivity.
  • Explore time-invariant systems and their characteristics in signal processing.
  • Research causal systems and their implications in real-time processing.
  • Learn about memoryless systems and how they differ from systems with memory.
USEFUL FOR

Students and professionals in electrical engineering, signal processing, and systems analysis who are looking to deepen their understanding of system properties and classifications.

dashkin111
Messages
47
Reaction score
0

Homework Statement


Is the following input/output (x is input, y is output) system linear, time invariant, causal, and memoryless? Answer yes or no for each one.

Homework Equations



y(t)=2x(t)+3

The Attempt at a Solution


My instinct tells me it's linear, but for some reason I have trouble showing it mathematically.It is linear if when you add scaled values of the input x(t), it equals the sum of the same scaled outputs. But it doesn't work out to be linear if I go by that definition
 
Last edited:
Physics news on Phys.org
LOL. Of course you can't prove it. It’s a trick question. The word linear is used differently in polynomial algebra and in signal processing.

In algebra a linear equation in one that is of the form y(t) = ax(t)+b.
In signal processing it is one that satisfies homogeneity and additivity. You are obviously talking signal processing (I recognize the language) so forget what you have learned about in algebra and apply the two tests up above. Clue: does cy(t) c(ax(t) +b) = acx(t) + b?
 
opps, I mean cy(t) = c(ax(t) +b) = acx(t) + b? Are they equal (of course not!)
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
Replies
1
Views
15K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
Replies
2
Views
5K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
11K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K