A principled approach to n-tuple recognition systems
A principled approach to n-tuple recognition systems
- Author(s): N.M. Allinson and A. Kolcz
- DOI: 10.1049/ic:19970125
For access to this article, please select a purchase option:
Buy conference paper PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
IEE Colloquium on Pattern Recognition — Recommend this title to your library
Thank you
Your recommendation has been sent to your librarian.
- Author(s): N.M. Allinson and A. Kolcz Source: IEE Colloquium on Pattern Recognition, 1997 page ()
- Conference: IEE Colloquium on Pattern Recognition
The idea of n-tuple sampling as a basis for pattern recognition, as proposed by Bledsoe and Browning (1959), remains a viable approach to a range of pattern classification tasks especially where speed of learning is of importance. The formal relationship between n-tuple neural networks and more mainstream network paradigms, such as radial basis function networks, and classical nonparametric pattern classifiers, such as kernel estimation, is considered, and it is described how the classic n-tuple recogniser and the n-tuple regression network form differing approximations in the classification process. (10 pages)
Inspec keywords: learning (artificial intelligence); pattern classification; neural nets
Subjects: Pattern recognition; Neural nets (theory); Signal processing and detection; Adaptive system theory
Related content
content/conferences/10.1049/ic_19970125
pub_keyword,iet_inspecKeyword,pub_concept
6
6