STRENGTH AND WEAKNESSES

Because an IIR filter uses both a feed-forward polynomialzeros as the roots) and a feedback polynomial (poles as theroots), it has a much sharper transition characteristic for agiven filter order. Like analog filters with poles, an IIR filterusually has nonlinear phase characteristics. Also, thefeedback loop makes IIR filters difficult to use in adaptivefilter applications.Due to its all zero structure, the FIR filter has a linear phaseresponse when the filter’s coefficients are symmetric, as isthe case in most standard filtering applications.
A FIR’simplementation noise characteristics are easy to model,especially if no intermediate truncation is used. In thiscommon implementation, the noise floor is at - 6.02 B + 6.02log2NdB where B is the number of actual bits used in thefilter’s coefficient quantization and N is again the filter order.This is why most Intersil filter ICs have more coefficient bitsthan data bits.An IIR filter’s poles may be close to or outside the unit circlein the Z plane.
This means an IIR filter may have stabilityproblems, especially after quantization is applied. An FIRfilter is always stable. FIR filters also allow development ofcomputationally efficient architectures in decimating orinterpolating applications, which will be described in moredetail later.