2) generate black noise (1/f3 deterministic signal over a 1,000 point interval). Black noise is the kind of noise you might encounter when modeling the frequency of natural disasters or blackbody radiation, and consists of mostly silence.
3) convolve both sources. Results in a signal with three distinct phases (over a 2,000 point interval). Demo conducted and plots made in Matlab.
The resulting plots are shown below. The associated Matlab code is located in my Github repository [4].
NOTES:
[1] an obscure reference from Saturday Night Live ("Makin' Copies" with Rob Schneider).
[2] Wellens, T., Shatokhin, V., and Buchleitner, A. Stochastic Resonance. Reports on Progress in Physics, 67(1), 45 (2004) AND Balenzuela, P. Braun, H., and Chialvo, D.R. The Ghost of Stochastic Resonance: An Introductory Review. arXiv, 1110.0136 (2011).
[3] For an artistic take on television static, please see TV Static Photos by Tom Moody and Ray Rapp. Examples of white noise in 2-D.
[4] this is part of work I am doing on an idea I am currently calling "noise strategies", a hybrid approach that merges game theory with the physics of noise. More on this in future posts.
[5] Alicea, B. Independent features of quantified thermocycling reactions (qRT-PCR). Figshare, doi:10.6084/m9.figshare.649432 (2013).
The analysis was done using FastICA 2.5 for MATLAB. For details, see the following paper: Hyvarinen, A. and Oja, E. Independent Component Analysis: Algorithms and Application. Neural Networks, 13(4-5), 411-430. (2000).
No comments:
Post a Comment