Skip to content Skip to navigation

Connexions

You are here: Home » Content » Filter Structures

Navigation

Recently Viewed

This feature requires Javascript to be enabled.

Filter Structures

Module by: Douglas L. Jones. E-mail the author

User rating (How does the rating system work?)
Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

:
(0 ratings)

Summary: Filter structures describe the computational sequence and data flow of a digital filter implementation.

Note: Your browser may not currently support MathML. See our browser support page for additional details. You can always view the correct math in the PDF version.

A realizable filter must require only a finite number of computations per output sample. For linear, causal, time-Invariant filters, this restricts one to rational transfer functions of the form Hz= b 0 + b 1 z-1++ b m z-m1+ a 1 z-1+ a 2 z-2++ a n z-n H z b 0 b 1 z b m z m 1 a 1 z a 2 z -2 a n z n Assuming no pole-zero cancellations, Hz H z is FIR if i,i>0: a i =0 i i 0 a i 0 , and IIR otherwise. Filter structures usually implement rational transfer functions as difference equations.

Whether FIR or IIR, a given transfer function can be implemented with many different filter structures. With infinite-precision data, coefficients, and arithmetic, all filter structures implementing the same transfer function produce the same output. However, different filter strucures may produce very different errors with quantized data and finite-precision or fixed-point arithmetic. The computational expense and memory usage may also differ greatly. Knowledge of different filter structures allows DSP engineers to trade off these factors to create the best implementation.

Content actions

Give Feedback:

E-mail the module author | Rate module ( How does the rating system work?)

Rating system

Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

(0 ratings)

Download:

Add module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections directly in Connexions. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need a Connexions account to use 'My Favorites'.

| A lens (?)

Definition of 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.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks