Lectures related to Self-organizing map

Explores how global order arises from local interactions in neural networks.

Covers the adaptation process in Kohonen maps using a nonlinear discriminant function and time-dependent correlation.

Covers feature maps, Representer theorem, kernels, and RKHS in machine learning.

Explores the K41 theory, discussing energy spectra, turbulence structure, and the role of dissipative scales in understanding turbulent flows.

Demonstrates efficient dot product computation and introduces nonlinear boundaries in the original space.