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Finite Difference Schemes

Finite Difference Schemes (FDSs) aim to solve differential equations by means of finite differences. For example, as discussed in §G.2, if $ y(t,x)$ denotes the displacement in meters of a vibrating string at time $ t$ seconds and position $ x$ meters, we may approximate the first- and second-order partial derivatives by

$\displaystyle {\dot y}(t,x)$ $\displaystyle \isdef$ $\displaystyle \frac{\partial}{\partial t}y(t,x) \;\approx\; \frac{y(t,x)-y(t-T,x)}{T}$  
$\displaystyle y'(t,x)$ $\displaystyle \isdef$ $\displaystyle \frac{\partial}{\partial x}y(t,x) \;\approx\; \frac{y(t,x)-y(t,x-X)}{X}$  
$\displaystyle {\ddot y}(t,x)$ $\displaystyle \isdef$ $\displaystyle \frac{\partial^2}{\partial t^2} y(t,x)
\;\approx\; \frac{y(t+T,x) - 2 y(t,x) + y(t-T,x) }{T^2}$  
$\displaystyle y''(t,x)$ $\displaystyle \isdef$ $\displaystyle \frac{\partial^2}{\partial x^2} y(t,x)
\;\approx\; \frac{y(t,x+X) - 2 y(t,x) + y(t,x-X) }{X^2}
\protect$ (L.1)

where $ T$ denotes the time sampling interval and $ X$ denotes the spatial sampling interval. These finite-difference approximations to the partial derivatives may be used to compute solutions of differential equations on a discrete grid:

x &\to& x_m&=& mX\nonumber \\
t &\to& t_n&=& nT\nonumber

Let us define an abbreviated notation for the grid variables

$\displaystyle y_{n,m}\isdef y(nT,mX)

and consider the ideal string wave equation (cf, §G.1):

$\displaystyle y''= \frac{1}{c^2}{\ddot y} \protect$ (L.2)

where $ c$ is a positive real constant (which turns out to be wave propagation speed). Then, as derived in §G.2, setting $ X=cT$ and substituting the finite-difference approximations into the ideal wave equation leads to the relation

$\displaystyle y_{n+1,m}+ y_{n-1,m}= y_{n,m+1}+ y_{n,m-1}

everywhere on the time-space grid (i.e., for all $ n$ and $ m$). Solving for $ y_{n+1,m}$ in terms of displacement samples at earlier times yields an explicit finite difference scheme for string displacement:

$\displaystyle y_{n+1,m}= y_{n,m+1}+ y_{n,m-1}- y_{n-1,m} \protect$ (L.3)

The FDS is called explicit because it was possible to solve for the state at time $ n$ as a function of the state at earlier times (and any other positions $ m$). This allows it to be implemented as a time recursion (or ``digital filter'') which computes a solution at time $ n$ from solution samples at earlier times (and any spatial positions). When an explicit FDS is not possible (e.g., a non-causal filter is derived), the discretized differential equation is said to define an implicit FDS. An implicit FDS can often be converted to an explicit FDS by a rotation of coordinates [50,458].

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[How to cite and copy this work] 
``Physical Audio Signal Processing for Virtual Musical Instruments and Digital Audio Effects'', by Julius O. Smith III, (December 2005 Edition).
Copyright © 2006-07-01 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
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