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Auditory experiments using cortical learning algorithms (CLA) and hierarchical temporal memory (HTM).
Note: These repositories currently are all work-in-progress.
Taken from the collection gathered via Gitter channel https://gitter.im/rcrowder/EncodingSpecificityPrinciple -
https://jp.mathworks.com/matlabcentral/answers/uploaded_files/23580/index.pdf Spectral Envelopes in Sound Analysis and Synthesis By Diemo Schwarz, Diplomarbeit Nr. 1622, IRCAM (Institut de la Recherche et Coordination Acoustique/Musique)
https://ccrma.stanford.edu/~jos/dft/
Mathematics of the Discrete Fourier Transform (DFT) with audio appliccations
By Julius O. Smith III, Center for Computer Research in Music and Acoustics (CCRMA)
http://www.dspguide.com/
The Scientist and Engineer's Guide to Digital Signal Processing
By Steven W. Smith, Ph.D.
http://www.eecs.qmul.ac.uk/~simond/pub/2012/PlumbleyDixon12-ima-tutorial-slides.pdf
Tutorial: Music Signal Processing
By Mark Plumbley and Simon Dixon, Centre for Digital Music (Queen Mary University of London)
An alternative for the encoding of audio signals is the modelling of spike firing of auditory-nerve fibers. A collection of models can be found in the EarLab @ Boston University (http://earlab.bu.edu/ See Modelling -> Downloadable Models). If you plan to use these models, beware of their history and limitations. For example, early models lack some necessary non-linearity in their responses.