Replace a device’s non-linear curve with its straight-line tangent at the Operating point, so small signals see a linear element. Every small-signal parameter in the course (, , , ) is a slope of some non-linear characteristic evaluated at Q. Learn the pattern once and it applies to the diode, the MOSFET, and the BJT without modification.

The Taylor-expansion justification

Take any non-linear device characteristic , say the Shockley exponential for a Diode or the square law for a MOSFET. Write the total voltage as a DC bias plus a small signal: . Taylor-expand about the bias point :

The first term is the DC current , the Operating point. The second term is linear in the signal , with constant coefficient , and that constant is the small-signal parameter (a conductance or transconductance). Everything from the third term on is non-linear distortion. The linear model is exactly the first two terms; keep them and throw away the rest.

That throwing-away is only legitimate if the discarded terms are negligible compared with the linear term. For the diode exponential, the ratio of the quadratic term to the linear term is . So the linear approximation is accurate provided

For a MOSFET the square law gives a hard validity scale of (Overdrive voltage). “Small signal” isn’t vague; it’s a quantitative bound set by the curvature of the device’s characteristic.

What linearisation produces

The slope at Q has a name and a finite value for each device:

Each is a derivative of a non-linear law evaluated at the bias point. Collect them into a Small-signal model and the device becomes a linear sub-circuit, which is what makes Small-signal analysis possible. This is also why Negative feedback helps: holding the device near a fixed operating point keeps the signal in the region where the tangent line is a good approximation, so distortion stays low. It’s the reason a non-linear device can be a faithful linear amplifier at all.