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2.8 Linear Symbolic Approximation 139<br />

In[22]:= DisplayForm[dvdmna]<br />

Out[22]//DisplayForm=<br />

1<br />

<br />

R1<br />

<br />

1<br />

R1<br />

0 1 <br />

V$1 0 <br />

<br />

1 1<br />

R1<br />

<br />

R1 <br />

1<br />

R2 <br />

1<br />

R3<br />

<br />

1<br />

R3<br />

0 V$2 0<br />

. ⩵⩵<br />

0 <br />

1<br />

1<br />

R3<br />

<br />

R3<br />

<br />

<br />

1<br />

R4<br />

0 V$3 0<br />

<br />

<br />

1 0 0 0<br />

I$V0 V0 <br />

<br />

Since we are interested in a simplified solution for the voltage at the output node 3, we specify V$3<br />

as the variable for which the equations are to be approximated.<br />

In[23]:= approxdvd = ApproximateMatrixEquation[dvdmna,<br />

V$3, dpdvd];<br />

DisplayForm[approxdvd]<br />

Out[24]//DisplayForm=<br />

0 0 0 1 <br />

1 1<br />

<br />

R1<br />

<br />

R1 V$1 0 <br />

<br />

1<br />

R2<br />

0 0 V$2 0<br />

0 <br />

1 1<br />

R3<br />

<br />

R3<br />

<br />

. ⩵⩵<br />

<br />

1<br />

R4<br />

0 V$3 0<br />

<br />

1 0 0 0 I$V0 V0 <br />

The result is a matrix equation from which all numerical irrelevant symbolic terms have been<br />

removed. We can now compute a simplified transfer function directly by solving the approximated<br />

equations.<br />

In[25]:= Solve[approxdvd, V$3]<br />

R2 R4 V0<br />

Out[25]= V$3 <br />

R1 R2 R3 R4 <br />

In this case, we obtain identical results from both equation-based and solution-based approximation.<br />

However, as opposed to the latter, equation-based approximation does not require an exact symbolic<br />

solution to be computed first. In such a small example this advantage makes nearly no difference,<br />

but it will turn out to be a key factor in larger applications.<br />

Approximating the Equations of the Amplifier<br />

As an example for a slightly larger application let’s continue with our well-known common-emitter<br />

amplifier once more. Again, we start by setting up a design point for<br />

ApproximateMatrixEquation, reusing the numerical values we defined for simplifying the exact<br />

solution with ApproximateTransferFunction. For matrix approximation, however, we still need<br />

some more numerical information. While the SAG algorithm approximates the coefficients of a<br />

transfer function independently, the SBG method uses the total value of a transfer function in<br />

a design point as reference quantity. Therefore, we must specify one or more particular frequency<br />

points at which ApproximateMatrixEquation should monitor the change in the value of the transfer<br />

function caused by the removal of terms.<br />

Here, we might be interested in computing a simplified expression describing the passband voltage<br />

gain of the amplifier. The Bode plot above shows that the passband extends from about Hz to<br />

several MHz, so we choose a design-point value for the operating frequency in the middle of the<br />

passband, e.g. at f ⩵ kHz. The corresponding value for the Laplace frequency s is then given by

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