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III. Gm-C Filtering - Epublications - Université de Limoges

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To estimate the influence of the distortion on a system, let’s expand, for small signal,<br />

the non-linear response with a Taylor series:<br />

2 3<br />

y = k0<br />

+ k1x<br />

+ k2<br />

x + k3<br />

x + ...<br />

(B.2)<br />

Introducing the previously <strong>de</strong>fined input signal, we get:<br />

With:<br />

y = Y + Y φ + Y cos( 2φ)<br />

+ Y cos( 3φ<br />

)<br />

(B.3)<br />

0<br />

1 cos 2<br />

3<br />

Y<br />

Y<br />

1<br />

0<br />

1 2<br />

= k0<br />

+ k2<br />

X<br />

2<br />

Y<br />

2<br />

1 2<br />

= k2<br />

X<br />

2<br />

= k1X<br />

+ k3<br />

X<br />

4<br />

Y<br />

3<br />

+ ...<br />

3 3<br />

1 3<br />

= k3<br />

X<br />

4<br />

+ ...<br />

- 189 -<br />

+ ...<br />

+ ...<br />

(B.4)<br />

(B.5)<br />

(B.6)<br />

(B.7)<br />

If the system were perfectly linear and without offset, only k1 would remain among all<br />

kis, since this factor corresponds to the gain of the system.<br />

For a non-linear system, the amplitu<strong>de</strong> of the fundamental Y1 is changed with the<br />

addition of a cubic term. Thus Y1 can be either smaller or larger than that obtained with a<br />

linear system. It is referred as an expansive characteristic when k3>0 and to a compressive<br />

characteristic when k3 0<br />

Figure 198. Expansion and compression point at 1dB<br />

Linear characteristic<br />

Non-linear characteristic<br />

k3 < 0<br />

X (log)

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