We study several complexity parameters for first order formulas and their suitability for first order learning models. We show that the standard notion of size is not captured by...
Developing a large belief network, like any large system, requires systems engineering to manage the design and construction process. We propose that network engineering follow a ...
A hybrid learning neuro-fuzzy system with asymmetric fuzzy sets (HLNFS-A) is proposed in this paper. The learning methods of random optimization (RO) and least square estimation (...
In this contribution, we present an algorithm for lowcomplexity global motion estimation, that works with block-coded video (e.g. MPEG-2). A superimposed global motion model is fi...
This paper discusses an extended adaptive supply network simulation model that explicitly captures growth (in terms of change in size over time, and birth and death) based on Utte...