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--------<br />

Sensitivities 101<br />

the corresponding impulse response time samples. Finally, the numerical<br />

convolution integral can be evaluated Jar arbitrary time functions specified at<br />

matching time samples. The memory requirements for practical problems<br />

usually fit easily into desktop computers having 8-32 kilobytes <strong>of</strong> randomaccess<br />

memory.<br />

The fast Fourier transform (FFT) must be mentioned before leaving this<br />

topic. It is clearly superior to the above and is available as standard s<strong>of</strong>tware<br />

from several desktop computer manufacturers. Serious users <strong>of</strong> the frequencyto-time-domain<br />

transform should consider special programs built around this<br />

technique, which are more efficient by at least an order <strong>of</strong> magnitude. It was<br />

not described because <strong>of</strong> its computational complexity.<br />

4.7. Sensitivities<br />

Sensitivity quantifies the relative change in a response function (Z) with<br />

respect to a relative change in anyone <strong>of</strong> several independent variables; i.e.,<br />

(4.80)<br />

for small changes in the klh variable x,. Often, Z is complex, and is evaluated<br />

at some given frequency. In this case, the sensitivity is also a complex number.<br />

For example, Z might be a ladder network input impedance, and x, might be<br />

an inductance value in microhenrys. Alternatively, Z might be a time function<br />

evaluated at some given time. Hopefully, a system being built will have<br />

sensitivities with magnitudes less than unity, otherwise it might react badly to<br />

component tolerances and to its environment.<br />

For each response, there are as many sensitivity numbers at a frequency or<br />

time value as there are variables in the problem. Applications include component<br />

tolerances, optimization (Chapter Five), and large-change calculations,<br />

e.g., network tuning. This section further defines real and complex sensitivities,<br />

relates them to partial derivatives, shows ways to obtain partial derivatives<br />

approximately by finite differences and exactly by Tellegen's theorem,<br />

and provides several examples. Most <strong>of</strong> the discussion is limited to the<br />

frequency domain, as justified in Section 4.7.4. Programs A2-1 and B4·1 will<br />

he used for calculations.<br />

4.7.1. Sensitivity Relationships. The partial derivative operator abbreviation<br />

(4.81 )<br />

will be used throughout. As the change in the variable, ~Xk'<br />

(4.80) approaches the common sensitivity definition<br />

Sz= x,~<br />

)(k<br />

zax k<br />

'<br />

approaches zero,<br />

(4.82)

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