Name
Title | ||
|---|---|---|
Neurocomputing Model for Computation of an Approximate Convex Hull of a Set of Points and Spheres |
Abstract | ||
|---|---|---|
In this letter, a two-layer neural network is proposed for computation of an approximate convex hull of a set of given points in 3-D or a set of spheres of different sizes. The algorithm is designed based on an elegant concept-shrinking of a spherical rubber balloon surrounding the set of objects in 3-D. Logically, a set of neurons is orderly placed on a spherical mesh i.e., on a rubber balloon surrounding the objects. Each neuron has a parameter vector associated with its current position. The resultant force of attraction between a neuron and each of the given points/objects, determines the direction of a movement of the neuron lying on the rubber balloon. As the network evolves, the neurons (parameter vectors) approximate the convex hull more and more accurately. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TNN.2007.891201 | IEEE Transactions on Neural Networks |
Keywords | Field | DocType |
approximation theory,neural nets,approximate convex hull,neurocomputing model,spherical rubber balloon,two-layer neural network,Convex hull,energy function,neural networks | Computer science,Approximation theory,Convex hull,Convex set,Natural rubber,Artificial intelligence,SPHERES,Artificial neural network,Resultant force,Machine learning,Computation | Journal |
Volume | Issue | ISSN |
18 | 2 | 1045-9227 |
Citations | PageRank | References |
1 | 0.38 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Srimanta Pal | 1 | 242 | 32.13 |
| Sabyasachi Bhattacharya | 2 | 10 | 2.82 |