Classification of reduction invariants with improved backpropagation

S. M. Shamsuddin, Maslina Darus, M. N. Sulaiman

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Data reduction is a process of feature extraction that transforms the data space into a feature space of much lower dimension compared to the original data space, yet it retains most of the intrinsic information content of the data. This can be done by using a number of methods, such as principal component analysis (PCA), factor analysis, and feature clustering. Principal components are extracted from a collection of multivariate cases as a way of accounting for as much of the variation in that collection as possible by means of as few variables as possible. On the other hand, backpropagation network has been used extensively in classification problems such as XOR problems, share prices prediction, and pattern recognition. This paper proposes an improved error signal of backpropagation network for classification of the reduction invariants using principal component analysis, for extracting the bulk of the useful information present in moment invariants of handwritten digits, leaving the redundant information behind. Higher order centralised scale- invariants are used to extract features of handwritten digits before PCA, and the reduction invariants are sent to the improved backpropagation model for classification purposes.

Original languageEnglish
Pages (from-to)239-247
Number of pages9
JournalInternational Journal of Mathematics and Mathematical Sciences
Volume30
Issue number4
DOIs
Publication statusPublished - 2002

Fingerprint

Back Propagation
Principal Component Analysis
Digit
Invariant
Moment Invariants
Data Reduction
Scale Invariant
Information Content
Principal Components
Factor Analysis
Feature Space
Classification Problems
Feature Extraction
Pattern Recognition
Clustering
Transform
Higher Order
Prediction
Model

ASJC Scopus subject areas

  • Mathematics (miscellaneous)

Cite this

Classification of reduction invariants with improved backpropagation. / Shamsuddin, S. M.; Darus, Maslina; Sulaiman, M. N.

In: International Journal of Mathematics and Mathematical Sciences, Vol. 30, No. 4, 2002, p. 239-247.

Research output: Contribution to journalArticle

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