By Topic

FPGA implementation of artificial neural networks: an application on medical expert systems

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

5 Author(s)

In this paper, the FPGA implementation of an Artificial Neural Networks (ANNs) composition for a Medical Expert System (MES) focused on pulmonary diseases is discussed. Using a specially designed neuron based on pipelined bit-serial arithmetic and a successful approximation of its determinant sigmoid function, a computation module has been structured that can accommodate eight (8) neurons in one FPGA. The use of memory elements allows for up to 256 K synapses to be mapped with high speed and great accuracy performances. Also, due to the FPGA reconfigurability, new structures and training patterns can be used to update this MES, in order to fit in more pulmonary or other diseases, with minimal effort

Published in:

Microelectronics for Neural Networks and Fuzzy Systems, 1994., Proceedings of the Fourth International Conference on

Date of Conference:

26-28 Sep 1994