title: Invariant set of weight of perceptron trained by perceptron training algorithm.
abstract: In this paper, an invariant set of the weight of the perceptron trained by the perceptron training algorithm is defined and characterized. The dynamic range of the steady-state values of the weight of the perceptron can be evaluated by finding the dynamic range of the weight of the perceptron inside the largest invariant set. In addition, the necessary and sufficient condition for the forward dynamics of the weight of the perceptron to be injective, as well as the condition for the invariant set of the weight of the perceptron to be attractive, is derived.
authors.affiliation: School of Mathematical Sciences, Queen Mary,University of London, E14NS London, UK. c.ho@qmul.ac.uk
authors.forename: Charlotte Yuk-Fan
authors.initials: CY
authors.lastname: Ho
authors.forename: Bingo Wing-Kuen
authors.initials: BW
authors.lastname: Ling
authors.forename: Herbert Ho-Ching
authors.initials: HH
authors.lastname: Iu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003661:Decision Support Techniques; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*