October 22nd - Filters
Digital filter design: IIR and FIR filters Analog EQ, Digital EQ
A Concise History of EQ
Variables in filters
 Types o o o
Low Pass
High Pass
Band Pass o
Parameters
 Q o o
Band Reject
Stands for ‘Quality Factor’
Defines the bandwidth and shape of the filter where a lower Q value is a broader shape across a wider range around the center frequency, and a higher Q value is a more narrow shape


Gain or Attenuation Amount
Center frequency
Analog
-no aliasing
-filters signals ahead of the ADC
-affects the phase of the signal. 45 degrees per pole (denominator)
Additional Resource on Analog Filter Design
Digital
-can be phase linear/constant time delay (FIR only)
-programmable with fine controls
-not influenced by temperature and tolerances
-only as good as the ADC
Source
Bessel Filters
-constant time delay in the pass band, but not surrounding bands
State-Variable Filters

 pre-massenberg parametric allowed for the development of the modern console

 show schematic where you pick up the signal in the circuit determines LP, HP, BP


 combine LP & BP to get band rejection show the LP/HP/BP/BR in a highlighted schematic filter resonance
Review of Transfer functions & Fourier analysis http://sites.tufts.edu/andrewrosen/files/2013/04/es3_final.pdf

Digital Filter Design (Pirkle, Chapters 6 & 8)

 coefficients of a filter determine its frequency response and other characteristics delay elements create phase shift as opposed to reactive components in analog circuits
 filters are often discussed in the visual domains; they are very similar (think instagram, photoshop, etc.) but utilized in a different part of the spectrum
IIR Filters

 infinite impulse response

 of called ‘linear filters’ essentially the same as SVF analog designs and interchangeable using BZT
 represent similar timbral and phase characteristics to analog filters
 problems: can easily become unstable and oscillate curve types (linkwitz-riley, butterworth, etc.)
FIR
 finite impulse response


 linear phase response non-linear filters
 most often implemented using convolution problems: pre-ringing
Additional resources:
Will Pirkle’s books, musicdsp.org
, webaudioapi , MATLAB for Audio, KVR developer’s section
Online Books, lecture links and class notes from CCRMA faculty http://mmckegg.github.io/web-audio-school/