Alternative Realizations

For actually implementing the example digital filter, we have only seen the difference equation

$$y(n) = x(n) + g_1\, x(n-M_1) - g_2\, y(n-M_2)$$

(from Eq. (3.1), diagrammed in Fig.3.1). While this structure, formally known as ``direct form I'', happens to be a good choice for digital comb filters, there are many other structures to consider in other situations. For example, it is often desirable, for numerical reasons, to implement low-pass, high-pass, and band-pass filters as series second-order sections. On the other hand, digital filters for simulating the vocal tract (for synthesized voice applications) are typically implemented as parallel second-order sections. (When the order is odd, there is one first-order section as well.) The coefficients of the first- and second-order filter sections may be calculated from the poles and zeros of the filter.

We will now illustrate the computation of a parallel second-order realization of our example filter $y(n) = x(n) + 0.5^3 x(n-3) - 0.9^5 y(n-5)$. As discussed above in §3.10, this filter has five poles and three zeros. We can use the partial fraction expansion (PFE), described in §6.8, to expand the transfer function into a sum of five first-order terms:

$$\begin{eqnarray*} H(z) &=& \frac{1 + 0.5^3 z^{-3}}{1 + 0.9^5 z^{-5}} \mathrel{=... ...+} \frac{0.4555 + 0.0922z^{-1}}{1 + 0.5562z^{-1}+ 0.8100z^{-2}}, \end{eqnarray*}$$

where, in the last step, complex-conjugate one-pole sections are combined into real second-order sections. Also, numerical values are given to four decimal places (so `$=$' is replaced by `$\approx$' in the second line). In the following subsections, we will plot the impulse responses and frequency responses of the first- and second-order filter sections above.