Self-Organizing Maps are models for unsupervised representation formation of cortical receptor fields by stimuli-driven self-organization in laterally coupled winner-take-all feedforward structures. This paper discusses modifications of the original Kohonen model that were motivated by a potential function, in their ability to set up a neural mapping of maximal mutual information. Enhancing the...

Image magnification algorithms directly affect the quality of image magnification. In this paper, based on the image interpolation algorithm principle, features of the nearest neighbor interpolation, bilinear interpolation, bicubic interpolation and cubic B spline interpolation were analyzed. At the same time, their advantages and disadvantages were compared. In the experiment, image magnificat...

We review observations and gravitational lensing theory related to the magnification of background QSOs by intervening overdensities, and the induced cross-correlation between sources and foreground galaxies. We pay special attention to simulations, and present some preliminary results from high resolution cluster simulations, which show the role of the halo core and substructure on non-linear ...

Magnification, the relative size of the neural representation of a portion of the visual field, decreases more rapidly with increasing visual field eccentricity in striate cortex than in the retinal ganglion cell layer of the owl monkey (Aotus trivirgatus); the proportion of the cells in striate cortex devoted to central vision is much larger than the comparable proportion of retinal ganglion c...

A new family of self-organizing maps, the Winner-Relaxing Kohonen Algorithm, is introduced as a generalization of a variant given by Kohonen in 1991. The magnification behaviour is calculated analytically. For the original variant a magnification exponent of 4/7 is derived; the generalized version allows to steer the magnification in the wide range from exponent 1/2 to 1 in the one-dimensional ...