WIT Press


Systolic Optimal Linear Associative Memory ANN Prototyping Using The Ptolemy Environment

Price

Free (open access)

Paper DOI

10.2495/HPC970291

Volume

18

Pages

11

Published

1997

Size

1,370 kb

Author(s)

T.H. Kaskalis, K.G. Margaritis & C.C. Tsouros

Abstract

This paper presents an example of how the Ptolemy environment can be used constructively to simulate prototypes of Artificial Neural Network algorithms, implemented by means of Systolic Array architectures. Initially, a number of well- known ANN algorithms, which all fall under the general concept of Associative Memory Artificial Neural Networks, is presented. Then, follows the discussion for the transformation and mapping of those algorithms onto a Linear Array Systolic architecture, capable of implementing all the discussed Associative Memory algo- rithms. Further, the Systolic Array architecture is designed and simulated using the Ptolemy Environment. Through graphical means, the user can easily obtain systo

Keywords