By Topic

Analog VLSI neural networks for impact signal processing

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

4 Author(s)
Brauch, J. ; Intel Corp., Santa Clara, CA, USA ; Tam, S.M. ; Holler, M.A. ; Shmurun, A.L.

The architecture and operation of the 80170NX electrically trainable analog neural network, which recognizes objects in real time, are discussed. The 80170NX uses a discrete Fourier transform (DFT) to preprocess an accelerometer output waveform that is subsequently recognized through a multilayer perceptron neural network. It is shown that neural network hardware operating in a linear mode can perform conventional signal processing functions. The similarity of neural network computations to linear signal processing functions makes it exceedingly straightforward to integrate neural networks and conventional signal processing in the system.<>

Published in:

Micro, IEEE  (Volume:12 ,  Issue: 6 )