Title :
Digital kernel perceptron
Author :
Anguita, D. ; Boni, A. ; Ridella, S.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Univ. of Genova, Italy
fDate :
5/9/2002 12:00:00 AM
Abstract :
It is shown that a kernel-based perceptron can be efficiently implemented in digital hardware using very few components. Despite its simplicity, the experimental results on standard data sets show remarkable performance in terms of generalisation error
Keywords :
large scale integration; learning systems; perceptrons; signal classification; VLSI-based learning systems; classification; digital hardware; digital kernel perceptron; generalisation error; performance; sonar data;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20020330
