DocumentCode
295863
Title
Placement with self-organising neural networks
Author
Zamani, M. Saheb ; Hellestrand, G.R.
Author_Institution
Sch. of Comput. Sci. & Eng., New South Wales Univ., Sydney, NSW, Australia
Volume
5
fYear
1995
fDate
Nov/Dec 1995
Firstpage
2185
Abstract
This paper introduces a neural network approach to node placement in an arbitrarily shaped rectilinear boundary based on self-organising principle. An abstract specification of the design is converted to a set of appropriate input vectors fed to the network at random. At the end of the process, the map shows the rectilinear shape 2-dimensional plane of the design in which the modules with higher connectivity to each other and also to some external ports are placed close to each other, hence minimising total connection length in the design
Keywords
circuit layout CAD; circuit optimisation; iterative methods; network topology; self-organising feature maps; 2D plane; Kohonen self organising map; abstract specification; input vectors; module connectivity; node placement; optimisation; self-organising neural networks; shaped rectilinear boundary; Circuits; Macrocell networks; Neural networks; Neurons; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487699
Filename
487699
Link To Document