By Topic

Neural computations as multidimensional feature mapping for acoustic information representation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Wang, K. ; Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA

Neurons in biological systems usually exhibit distinctive response selectivity to certain features in the stimulus. As the neurons are functionally and spatially segregated, one may interpret the computational principles of the neural systems as a mechanism of feature mapping, which represents information in a topographic fashion. In this article, the author summarizes the physiological findings of the neural selectivities in the primary auditory cortex and, based on which, proposes a mathematical framework for mapping the acoustic features conveyed in the power spectrum. The author further demonstrates how this model may be employed to explain a series of psychoacoustic experiments that are designed to measure the sensitivity of the human auditory system to spectral shape perception, and hypothesizes how the measured thresholds may be related to the model parameters

Published in:

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on  (Volume:7 )

Date of Conference:

27 Jun-2 Jul 1994