By Topic

Applications of neural-network (NN) signal processing in brain research

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

2 Author(s)
Gevins, A.S. ; EEG Syst. Lab., San Francisco, CA, USA ; Morgan, N.H.

The application is reviewed of neural-network (NN) signal processing methods to neurological waveform detection and pattern analysis. NN methods are shown to be an excellent way of incorporating expert knowledge about the brain into a mathematical framework with minimal assumptions about the statistics of signal and noise. Constrained by expert knowledge, NN algorithms can search for optimal and near-optimal connections between, and weightings of, application specific features in data spaces for which human knowledge is incomplete. Applying NN algorithms to electrical signals noninvasively recorded from the human brain, the neurological effects of different types of sleeping pills have been differentiated, and insights have been gained as to how our brains produce higher cognitive functions

Published in:

Acoustics, Speech and Signal Processing, IEEE Transactions on  (Volume:36 ,  Issue: 7 )