This toolbox implements functions for clustering and for evaluating clustering algorithms.

Simulation of 8000 Triangulated boxes in a rotating container. Clearly visible are the more stable corner packing's that take longer to collapse and form the...

CUDA SDK example modification for mechanical process modelling.

Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithm they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity.