Cabinet Filtering

International Standard Book Number — Click for https://mathworld.wolfram.com/ISBN.html

Faust (Functional AUdio STream language) is a language for real-time audio signal processing that compiles into C++ for a variety of platforms. — Click for https://faust.grame.fr/

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Matlab is a high-level scripting language for scientific computing — Click for https://ccrma.stanford.edu/~jos/matlab/

The invfreqz function (in matlab) computes the coefficients of a recursive digital filter based on specified frequency-response samples. — Click for http://www.dsprelated.com/showcode/20.php

A digital filter can be visualized as a 'black box' that accepts a sequence of numbers and emits a new sequence of numbers. In digital audio signal processing applications, such number sequences usually represent sounds. For example, digital filters are used to implement graphic equalizers and other digital audio effects. — Click for https://ccrma.stanford.edu/~jos/filters/

The frequency response is defined for LTI filters as the Fourier transform of the filter output signal divided by the Fourier transform of the filter input signal — Click for https://ccrma.stanford.edu/~jos/filters/Frequency_Response_I.html

The impulse response of a system is its output signal in response to the impulse signal. For discrete time (digital) systems, the impulse is a 1 followed by zeros. In continuous time, the impulse is a narrow, unit-area pulse (ideally infinitely narrow). — Click for https://ccrma.stanford.edu/~jos/filters/Impulse_Response_Representation.html

A signal is typically a real-valued function of time. A discrete-time signal is typically a real-valued function of discrete time, and is therefore a time-ordered sequence of real numbers. — Click for http://ccrma.stanford.edu/~jos/filters/Definition_Signal.html

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A filter in the audio signal processing context is any operation that accepts a signal as an input and produces a signal as an output. Most practical audio filters are linear and time invariant, in which case they can be characterized by their impulse response or their frequency response. — Click for https://ccrma.stanford.edu/~jos/filters/What_Filter.html

Cabinet Filtering

The distortion output signal is often further filtered by an amplifier cabinet filter, representing the enclosure, driver responses, etc. It is straightforward to measure the impulse response (or frequency response) of a speaker cabinet and fit it with a recursive digital filter design function such as invfreqz in matlab (§8.6.4). Individual speakers generally have one major resonance--the ``cone resonance''--which is determined by the mass, compliance, and damping of the driver subassembly. The enclosing cabinet introduces many more resonances in the audio range, generally tuned to even out the overall response as much as possible.

Cabinet Filtering

``Physical Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2010, ISBN 978-0-9745607-2-4 Copyright © 2024-06-28 by Julius O. Smith III Center for Computer Research in Music and Acoustics (CCRMA), Stanford University

``Physical Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2010, ISBN 978-0-9745607-2-4
Copyright © 2024-06-28 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA), Stanford University