An approach to evolvable neural functionality.
Capanni, Niccolo; MacLeod, Christopher; Maxwell, Grant
This paper outlines a neural model, which has been designed to be flexible enough to assume most mathematical functions. This is particularly useful in evolutionary networks as it allows the network complexity to increase without adding neurons. Theory and results are presented, showing the development of both time series and non-time dependent applications.
|Presentation Conference Type||Conference Paper (unpublished)|
|Start Date||Jun 26, 2003|
|Publication Date||Dec 31, 2003|
|Institution Citation||CAPANNI, N., MACLEOD, C. and MAXWELL, G. 2003. An approach to evolvable neural functionality. Presented at the 2003 Joint International conference on artificial neural networks and neural information processing (ICANN/ICONIP 2003), 26-29 June 2003, Istanbul, Turkey.|
|Keywords||Evolutionary networks; Neural functionality; Artificial neural networks|
CAPANNI 2003 An approach to evolvable