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FDN and State Space Descriptions

When $ M_1=M_2=M_3=1$ in Eq.$ \,$(2.10), the FDN (Fig.2.28) reduces to a normal state-space model1.3.7),

$\displaystyle \mathbf{x}(n+1)$ $\displaystyle =$ $\displaystyle \mathbf{A}\, \mathbf{x}(n) + \mathbf{u}_+(n)$  
$\displaystyle \mathbf{y}_+(n)$ $\displaystyle =$ $\displaystyle \mathbf{x}(n)
\protect$ (3.11)

The matrix $ \mathbf{A}={\bm \Gamma}\mathbf{Q}$ is the state transition matrix. The vector $ \mathbf{x}(n) = [x_1(n), x_2(n), x_3(n)]^T$ holds the state variables that determine the state of the system at time $ n$. The order of a state-space system is equal to the number of state variables, i.e., the dimensionality of $ \mathbf{x}(n)$. The input and output signals have been trivially redefined as

\begin{eqnarray*}
\mathbf{u}_+(n) &\isdef & \mathbf{u}(n+1)\\
\mathbf{y}_+(n) &\isdef & \mathbf{y}(n+1)
\end{eqnarray*}

to follow normal convention for state-space form.

Thus, an FDN can be viewed as a generalized state-space model for a class of $ N$th-order linear systems--``generalized'' in the sense that unit delays are replaced by arbitrary delays. This correspondence is valuable for analysis because tools for state-space analysis are well known and included in many software libraries such as with matlab.


Previous: Feedback Delay Networks (FDN)
Next: Single-Input, Single-Output (SISO) FDN

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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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