Connexions

You are here: Home » Content » Overview of Digital Filter Design
Content Actions
Lenses

What is a lens?

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

This content is ...
Affiliated with (?)
This content is either by members of the organizations listed or about topics related to the organizations listed. Click each link to see a list of all content affiliated with the organization.
  • This module is included inLens: Rice University OpenCourseWare
    By: OpenCourseWare ConsortiumAs a part of collection:"Digital Filter Design"

    Click the "Rice University OCW" link to see all content affiliated with them.

    Rice University OCW
Tags

(?)

These tags come from the endorsement, affiliation, and other lenses that include this content.

Overview of Digital Filter Design

Module by: Douglas L. Jones

    Advantages of FIR filters
  1. Straight forward conceptually and simple to implement
  2. Can be implemented with fast convolution
  3. Always stable
  4. Relatively insensitive to quantization
  5. Can have linear phase (same time delay of all frequencies)
    Advantages of IIR filters
  1. Better for approximating analog systems
  2. For a given magnitude response specification, IIR filters often require much less computation than an equivalent FIR, particularly for narrow transition bands
Both FIR and IIR filters are very important in applications.
    Generic Filter Design Procedure
  1. Choose a desired response, based on application requirements
  2. Choose a filter class
  3. Choose a quality measure
  4. Solve for the filter in class 2 optimizing criterion in 3

Perspective on FIR filtering

Most of the time, people do L L optimal design, using the Parks-McClellan algorithm. This is probably the second most important technique in "classical" signal processing (after the Cooley-Tukey (radix-2) FFT).
Most of the time, FIR filters are designed to have linear phase. The most important advantage of FIR filters over IIR filters is that they can have exactly linear phase. There are advanced design techniques for minimum-phase filters, constrained L 2 L 2 optimal designs, etc. (see chapter 8 of text). However, if only the magnitude of the response is important, IIR filers usually require much fewer operations and are typically used, so the bulk of FIR filter design work has concentrated on linear phase designs.

Comments, questions, feedback, criticisms?

Send feedback