A system is homogeneous if multiplying the input by any constant multiplies the output by the same constant . In symbols: if , then , for any input and any constant (including complex constants).

Pictorially: if you run through the system and get , then running through must give exactly — not plus a little extra, not .

This has to hold for every and every , not just some specific choice.

How to test

Apply the system’s defining rule to two inputs and compare:

  1. Pick arbitrary . Find .
  2. Pick . Find .
  3. Check whether . If yes for every and , the system is homogeneous.

Worked examples

: Let , . Let , . Is ? Only in trivial cases — so not homogeneous. Intuition: doubling the input of an exponential doesn’t double the output, it squares it. The exponential is fundamentally nonlinear.

: gives ; gives . But , which equals only if . So not homogeneous.

The second example is more surprising. “Add 2 to the input” looks innocent — an affine offset, basically linear from an engineer’s perspective. But it fails homogeneity, because the constant 2 doesn’t scale with the input.

The lesson

A system that includes a “DC offset” or any input-independent contribution is not homogeneous. Homogeneity requires that “no input” produces “no output” — the rule is purely about transforming the input, with no extras on top.

Homogeneity is one of the two ingredients of linearity; the other is additivity. Together they give the LTI property when combined with Time-invariance.