title: Sharpening of input excitation curves in lateral inhibition.
abstract: Various lateral inhibition neural networks are studied by means of computer simulation regarding their ability to sharpen the input excitation curves. To quantify this ability we introduced two new entropy-like quantities (called the iteration entropy and the rate of convergence) which represent suitable measures for the sharpening of the input excitation curves in a certain lateral inhibition neural network. Using these quantities we quantitatively described the sharpening ability of different lateral inhibition networks.
authors.affiliation: Institute of Mathematics, Slovak Academy of Sciences, Bratislava, Czecho-Slovakia.
authors.forename: V
authors.initials: V
authors.lastname: Majernik
authors.forename: A
authors.initials: A
authors.lastname: Kral
mesh_terms: D009433:Neural Inhibition; D016571:Neural Networks, Computer; D009474:Neurons; D011336:Probability