noises.lib
Noises library. Its official prefix is no.
This library provides various noise generators and stochastic signal sources for audio synthesis and testing. It includes white, pink, brown, and blue noise, as well as pseudo-random number generators and utilities for decorrelated signals and random modulation in Faust DSP programs.
The Noises library is organized into 1 section:
References
Functions Reference
(no.)noise
White noise generator (outputs random number between -1 and 1).
noise is a standard Faust function.
Usage
noise : _
Where:
- output: white noise signal in [-1, 1].
Test
no = library("noises.lib");
noise_test = no.noise;
(no.)multirandom
Generates multiple decorrelated random numbers in parallel.
Usage
multirandom(N) : si.bus(N)
Where:
N: the number of decorrelated random numbers in parallel, a constant numerical expression
Test
no = library("noises.lib");
multirandom_test = no.multirandom(4);
(no.)multinoise
Generates multiple decorrelated noises in parallel.
Usage
multinoise(N) : si.bus(N)
Where:
N: the number of decorrelated random numbers in parallel, a constant numerical expression
Test
no = library("noises.lib");
multinoise_test = no.multinoise(3);
(no.)noises
A convenient wrapper around multinoise.
Usage
noises(N,i) : _
Where:
N: the number of decorrelated random numbers in parallel, a constant numerical expressioni: the selected random number (i in [0..N[)
Test
no = library("noises.lib");
noises_test = no.noises(4, 2);
(no.)dnoise
A deterministic noise burst with a dynamically adjustable seed, enabling consistent recall. Useful for noise variation sensitive applications like replicable/recallable percussion sounds and waveguide excitation.
Usage
dnoise(t,sx) : _
Where:
t: is a noise burst triggersx: defines the range of integer seed multipliers.
Test
no = library("noises.lib");
ba = library("basics.lib");
dnoise_test = (1 : ba.impulsify, 10.0) : no.dnoise;
Example
This expression sx = hslider("seed multiplier",1,1,1000,1) allows 1000 distinct seed variations.
To generate a burst with a fixed length, use ba.spulse(bLength, t) (as trigger for the t parameter), where bLength is the burst duration in samples and t is a trigger.
(no.)randomseed
A random seed based on the foreign function arc4random
(see man arc4random). Used in rnoise, rmultirandom, etc. to
avoid having the same pseudo random sequence at each run.
WARNING: using the foreign function arc4random, so only available in C/C++ and LLVM backends.
Usage
randomseed : _
Where:
- output: platform-specific random seed value.
Test
no = library("noises.lib");
randomseed_test = no.randomseed;
(no.)rnoise
A randomized white noise generator (outputs random number between -1 and 1).
WARNING: using the foreign function arc4random, so only available in C/C++ and LLVM backends.
Usage
rnoise : _
Test
no = library("noises.lib");
rnoise_test = no.rnoise;
(no.)rmultirandom
Generates multiple decorrelated random numbers in parallel.
WARNING: using the foreign function arc4random, so only available in C/C++ and LLVM backends.
Usage
rmultirandom(N) : _
Where:
N: the number of decorrelated random numbers in parallel, a constant numerical expression
Test
no = library("noises.lib");
rmultirandom_test = no.rmultirandom(4);
(no.)rmultinoise
Generates multiple decorrelated noises in parallel.
WARNING: using the foreign function arc4random, so only available in C/C++ and LLVM backends.
Usage
rmultinoise(N) : _
Where:
N: the number of decorrelated random numbers in parallel, a constant numerical expression
Test
no = library("noises.lib");
rmultinoise_test = no.rmultinoise(3);
(no.)rnoises
A convenient wrapper around rmultinoise.
WARNING: using the foreign function arc4random, so only available in C/C++ and LLVM backends.
Usage
rnoises(N,i) : _
Where:
N: the number of decorrelated random numbers in paralleli: the selected random number (i in [0..N[)
Test
no = library("noises.lib");
rnoises_test = no.rnoises(4, 2);
(no.)pink_noise
Pink noise (1/f noise) generator (third-order approximation covering the audio band well).
pink_noise is a standard Faust function.
Usage
pink_noise : _
Where:
- output: pink (1/f) noise signal.
Test
no = library("noises.lib");
pink_noise_test = no.pink_noise;
Alternatives
Higher-order approximations covering any frequency band can be obtained using
no.noise : fi.spectral_tilt(order,lowerBandLimit,Bandwidth,p)
where p=-0.5 means filter rolloff f^(-1/2) which gives 1/f rolloff in the
power spectral density, and can be changed to other real values.
Example
pink_noise_compare.dsp - compare three pinking filters
process = pink_noises with {
f0 = 35; // Lower bandlimit in Hz
bw3 = 0.7 * ma.SR/2.0 - f0; // Bandwidth in Hz, 3rd order case
bw9 = 0.8 * ma.SR/2.0 - f0; // Bandwidth in Hz, 9th order case
pink_tilt_3 = fi.spectral_tilt(3,f0,bw3,-0.5);
pink_tilt_9 = fi.spectral_tilt(9,f0,bw9,-0.5);
pink_noises = 1-1' <:
no.pink_filter, // original designed by invfreqz in Octave
pink_tilt_3, // newer method using the same filter order
pink_tilt_9; // newer method using a higher filter order
};
Output of Example
faust2octave pink_noise_compare.dsp
Octave:1> semilogx(20*log10(abs(fft(faustout,8192))(1:4096,:)));
...
References
(no.)pink_noise_vm
Multi pink noise generator.
Usage
pink_noise_vm(N) : _
Where:
N: number of latched white-noise processes to sum, not to exceed sizeof(int) in C++ (typically 32).
Test
no = library("noises.lib");
pink_noise_vm_test = no.pink_noise_vm(4);
References
- http://www.dsprelated.com/showarticle/908.php
- http://www.firstpr.com.au/dsp/pink-noise/#Voss-McCartney
(no.)lfnoise, (no.)lfnoise0 and (no.)lfnoiseN
Low-frequency noise generators (Butterworth-filtered downsampled white noise).
Usage
lfnoise0(rate) : _ // new random number every int(ma.SR/rate) samples or so
lfnoiseN(N,rate) : _ // same as "lfnoise0(rate) : fi.lowpass(N,rate)" [see filters.lib]
lfnoise(rate) : _ // same as "lfnoise0(rate) : seq(i,5,fi.lowpass(N,rate))" (no overshoot)
Example
(view waveforms in faust2octave):
rate = ma.SR/100.0; // new random value every 100 samples (ma.SR from maths.lib)
process = lfnoise0(rate), // sampled/held noise (piecewise constant)
lfnoiseN(3,rate), // lfnoise0 smoothed by 3rd order Butterworth LPF
lfnoise(rate); // lfnoise0 smoothed with no overshoot
Test
no = library("noises.lib");
lfnoise0_test = no.lfnoise0(10.0);
lfnoiseN_test = no.lfnoiseN(3, 10.0);
lfnoise_test = no.lfnoise(10.0);
(no.)sparse_noise
Sparse noise generator.
Usage
sparse_noise(f0) : _
Where:
f0: average frequency of noise impulses per second
Random impulses in the amplitude range -1 to 1 are generated at an average rate of f0 impulses per second.
Test
no = library("noises.lib");
sparse_noise_test = no.sparse_noise(5.0);
References
- See velvet_noise
(no.)velvet_noise_vm
Velvet noise generator.
Usage
velvet_noise(amp, f0) : _
Where:
amp: amplitude of noise impulses (positive and negative)f0: average frequency of noise impulses per second
Test
no = library("noises.lib");
velvet_noise_test = no.velvet_noise(0.5, 5.0);
References
- Matti Karjalainen and Hanna Jarvelainen, "Reverberation Modeling Using Velvet Noise", in Proc. 30th Int. Conf. Intelligent Audio Environments (AES07), March 2007.
(no.)gnoise
Approximate zero-mean, unit-variance Gaussian white noise generator.
Usage
gnoise(N) : _
Where:
N: number of uniform random numbers added to approximate Gaussian white noise
Test
no = library("noises.lib");
gnoise_test = no.gnoise(8);
References
- See Central Limit Theorem
(no.)colored_noise
Generates a colored noise signal with an arbitrary spectral roll-off factor (alpha) over the entire audible frequency range (20-20000 Hz). The output is normalized so that an equal RMS level is maintained for different values of alpha.
Usage
colored_noise(N,alpha) : _
Where:
N: desired integer filter order (constant numerical expression)alpha: slope of roll-off, between -1 and 1. -1 corresponds to brown/red noise, -1/2 pink noise, 0 white noise, 1/2 blue noise, and 1 violet/azure noise.
Test
no = library("noises.lib");
colored_noise_test = no.colored_noise(4, 0.0);
Examples
See dm.colored_noise_demo.