5 - FIR filter approximations

Summary

Introduction

In this chapter we will study the approximation schemes for digital filters with FIR and we will present the methods for determining the multiplier coefficients and the filter order, in such a way that the resulting frequency response satisfies a set of prescribed specifications.

In some cases, FIR filters are considered inefficient, in the sense that they require a high-order transfer function to satisfy the system requirements when compared with the order required by IIR digital filters. However, FIR digital filters do possess a few implementation advantages, such as a possible exact linear-phase characteristic and intrinsically stable implementations, when using nonrecursive realizations. In addition, the computational complexity of FIR digital filters can be reduced if they are implemented using fast numerical algorithms such as the FFT.

We start by discussing the ideal frequency response characteristics of commonly used FIR filters, as well as their corresponding impulse responses. We include lowpass, highpass, bandpass, and bandstop filters in the discussion, and also treat two other important filters, namely differentiators and Hilbert transformers.

We go on to discuss the frequency sampling and the window methods for approximating FIR digital filters, focusing on the rectangular, triangular, Bartlett, Hamming, Blackman, Kaiser, and Dolph–Chebyshev windows. In addition, the design of maximally flat FIR filters is addressed.

Following this, numerical methods for designing FIR filters are discussed. A unified framework for the general approximation problem is provided.