K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...
We consider the problem of representing, in a space-efficient way, a function f : S → Σ such that any function value can be computed in constant time on a RAM. Specifically, ou...
This paper gives a widely applicable technique for solving many of the parameter estimation problems encountered in geometric computer vision. A commonly used approach is to minim...
In this paper, we look at the problem of inverter minimization in multi-level logic networks. The network is specified in terms of a set of base functions and the inversion opera...
Abstract--This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural netw...