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More General Finite-Difference Methods

The FDA and bilinear transform of the previous sections can be viewed as first-order conformal maps from the analog $ s$ plane to the digital $ z$ plane. These maps are one-to-one and therefore non-aliasing. The FDA performs well at low frequencies relative to the sampling rate, but it introduces artificial damping at high frequencies. The bilinear transform preserves the frequency axis exactly, but over a warped frequency scale. Being first order, both maps preserve the number of poles and zeros in the model.

We may only think in terms of mapping the $ s$ plane to the $ z$ plane for linear, time-invariant systems. This is because Laplace transform analysis is not defined for nonlinear and/or time-varying differential equations (no $ s$ plane). Therefore, such systems are instead digitized by some form of numerical integration to produce solutions that are ideally sampled versions of the continuous-time solutions. It is often necessary to work at sampling rates much higher than the desired audio sampling rate, due to the bandwidth-expanding effects of nonlinear elements in the continuous-time system.

A tutorial review of numerical solutions of Ordinary Differential Equations (ODE), including nonlinear systems, with examples in the realm of audio effects (such as a diode clipper), is given in [555]. Finite difference schemes specifically designed for nonlinear discrete-time simulation, such as the energy-preserving ``Kirchoff-Carrier nonlinear string model'' and ``von Karman nonlinear plate model'', are discussed in [53].

The remaining sections here summarize a few of the more elementary techniques discussed in [555].



Subsections
Previous: Limitations of Lumped Element Digitization
Next: General Nonlinear ODE

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About the Author: Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See http://ccrma.stanford.edu/~jos/ for details.


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