2006 | OriginalPaper | Chapter
FPGA Implementation of Very Large Associative Memories
Application to Automatic Speech Recognition
Authors : Dan Hammerstrom, Changjian Gao, Shaojuan Zhu, Mike Butts
Published in: FPGA Implementations of Neural Networks
Publisher: Springer US
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Associative networks have a number of properties, including a rapid, compute efficient best-match and intrinsic fault tolerance, that make them ideal for many applications. However, large networks can be slow to emulate because of their storage and bandwidth requirements. In this chapter we present a simple but effective model of association and then discuss a performance analysis we have done in implementing this model on a single high-end PC workstation, a PC cluster, and FPGA hardware.