Digital Waveguide Oscillator Example Next  |  Prev  |  Up  |  Top  |  Index  |  JOS Index  |  JOS Pubs  |  JOS Home  |  Search

State-Space Analysis Example:
The Digital Waveguide Oscillator

As an example of state-space analysis, we will use it to determine the frequency of oscillation of the system of Fig.E.3 [90].

Figure E.3: The second-order digital waveguide oscillator.
\begin{figure}\input fig/sswgo.pstex_t

Note the assignments of unit-delay outputs to state variables $ x_1(n)$ and $ x_2(n)$. From the diagram, we see that

$\displaystyle x_1(n+1) = c[x_1(n) + x_2(n)] - x_2(n) = c\,x_1(n) + (c-1) x_2(n)


$\displaystyle x_2(n+1) = x_1(n) + c[x_1(n) + x_2(n)] = (1+c) x_1(n) + c\,x_2(n)

In matrix form, the state time-update can be written

$\displaystyle \left[\begin{array}{c} x_1(n+1) \\ [2pt] x_2(n+1) \end{array}\rig...
...ay}\right]}_A \left[\begin{array}{c} x_1(n) \\ [2pt] x_2(n) \end{array}\right]

or, in vector notation,

$\displaystyle {\underline{x}}(n+1) = A \, {\underline{x}}(n).

We have two natural choices of output, $ x_1(n)$ and $ x_2(n)$:

y_1(n) &\isdef & x_1(n) = [1, 0] {\underline{x}}(n)\\
y_2(n) &\isdef & x_2(n) = [0, 1] {\underline{x}}(n)

A basic fact from linear algebra is that the determinant of a matrix is equal to the product of its eigenvalues. As a quick check, we find that the determinant of $ A$ is

$\displaystyle \det{A} = c^2 - (c+1)(c-1) = c^2 - (c^2-1) = 1.

Since an undriven sinusoidal oscillator must not lose energy, and since every lossless state-space system has unit-modulus eigenvalues (consider the modal representation), we expect $ \left\vert\det{A}\right\vert=1$.

Note that $ {\underline{x}}(n) = A^n{\underline{x}}(0)$. If we diagonalize this system to obtain $ \tilde{A}=E^{-1}A E$, where $ \tilde{A}=$   diag$ [\lambda_1,\lambda_2]$, and $ E$ is the matrix of eigenvectors of $ A$, then we have

$\displaystyle \underline{{\tilde x}}(n) = \tilde{A}^n\,\underline{{\tilde x}}(0...
...t[\begin{array}{c} {\tilde x}_1(0) \\ [2pt] {\tilde x}_2(0) \end{array}\right]

where $ \underline{{\tilde x}}(n) \isdef E^{-1}{\underline{x}}(n)$ denotes the state vector in these new ``modal coordinates''. Since $ \tilde{A}$ is diagonal, the modes are decoupled, and we can write

{\tilde x}_1(n) &=& \lambda_1^n\,{\tilde x}_1(0)\\
{\tilde x}_2(n) &=& \lambda_2^n\,{\tilde x}_2(0).

If this system is to generate a real sampled sinusoid at radian frequency $ \omega$, the eigenvalues $ \lambda_1$ and $ \lambda_2$ must be of the form

\lambda_1 &=& e^{j\omega T}\\
\lambda_2 &=& e^{-j\omega T},

(in either order) where $ \omega$ is real, and $ T$ denotes the sampling interval in seconds.

Thus, we can determine the frequency of oscillation $ \omega$ (and verify that the system actually oscillates) by determining the eigenvalues $ \lambda_i $ of $ A$. Note that, as a prerequisite, it will also be necessary to find two linearly independent eigenvectors of $ A$ (columns of $ E$).

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``Introduction to Digital Filters with Audio Applications'', by Julius O. Smith III, (August 2006 Edition).
Copyright © 2007-02-02 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
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