Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
ional models of cortical associative memory often take a top-down approach. We have previously described such an abstract model with a hypercolumnar structure. Here we explore a s...
Effectively managing a supply chain requires visibility to detect unexpected variations in the dynamics of the supply chain environment at an early stage. This paper proposes a me...
Alfonso Sarmiento, Luis Rabelo, Ramamoorthy Lakkoj...
We study a model of feature binding in prefrontal cortex which defers specific perceptual information to lower areas and merely maintains the identity of the combination. The mod...
Hecke Schrobsdorff, J. Michael Herrmann, Theo Geis...
The use of motor primitives for the generation of complex movements is a relatively new and interesting idea for dimensionality reduction in robot control. We propose a framework ...