Abstract
System response data are frequently analysed by fitting with a trigonometric Fourier series. However, the trigonometric series is not necessarily the best choice since the number of terms required to give a desired integral-square error (i.s.e.) fit may be excessive and may not provide the intuitive feeling for the system-response poles. A general method is given wherebya priori orposteriori information about the system poles may be used to fit the data with a small number of terms and satisfy i.s.e. criteria. An application example shows a three-term series that fitted biological stretch-receptor step-response data with two terms other than d.c. and yielded an i.s.e. of only 0·5 to 1·2% for the non-d.c. data.
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