Skip to content Skip to navigation

Connexions

You are here: Home » Content » Approaching Good Distortion

Navigation

Content Actions

  • Download module PDF
  • Add to ...
    Add the module to:
    • My Favorites
    • A lens
    • An external social bookmarking service
    • My Favorites (What is '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 (What is 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
  • E-mail the authors
  • Rate this 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)

Lenses

What is 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.

This content is ...

Affiliated with (What does "Affiliated with" mean?)

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.
  • Rice University ELEC 301 Projects

    This module is included inLens: Rice University ELEC 301 Project Lens
    By: Rice University ELEC 301As a part of collection:"ECE 301 Projects Fall 2003"

    Click the "Rice University ELEC 301 Projects" link to see all content affiliated with them.

Recently Viewed

This feature requires Javascript to be enabled.

Approaching Good Distortion

Module by: Elizabeth Gregory, Jason Buck

Summary: Discovering quirks in MATLAB, finding a simple noise filter, and getting great sound!

Creating the Distortion

As we discovered in Problems with Distortion, when we work with the modified power series, we do not get the expected result. In fact, we only get a lower quality version of our original sound file! However, taking a look at the minimum and maximum of our sound vector, we soon discover the problem: all values of our signal are between 1 and -1! When we take these numbers to the ten power, or even the five power, all we do is make our sound values smaller. Therefore, a quick fix would be to take these numbers to the one-tenth power or the one-fifth power, in effect dividing each power by ten. Upon checking out our signal, we get the wonderful distortion that we needed! As we play around with different coefficients and powers (all less than one), our own discerning ears determine which coefficients and powers are best for the distortion we want. However, in all of this playing around, a particular evil has crept in among our distortion: noise!

Dealing with the Noise

Several different methods can be used to take out the noise from our signal. In fact, an entire project was dedicated to noise-elimination in 2002. However, since this project focuses mainly on a MATLAB approach rather than a C approach, we'll leave implimenting that noise filter to a more adventurous group.

The simplest way to get rid of the noise would be to impliment a band pass filter in MATLAB, allowing only for the frequency range of the guitar (about 100Hz to about 4000Hz, perhaps higher depending on the high notes you play). This filter will get rid of most of the noise, except for the noise that lies within those frequencies.

Another easy way to get rid of the noise involves the FFT. After taking the FFT of the signal, you can decrease noise by throwing out the frequencies below a certain threshold.

Comments, questions, feedback, criticisms?

Send feedback