A new approach for designing self-organizing systems and application to adaptive control

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed

The Equation of State and Quark Number Susceptibility in Hard-Dense-Loop Approximation

Based on the method proposed in [ H. S. Zong, W. M. Sun, Phys. Rev. \textbf{D 78}, 054001 (2008)], we calculate the equation of state (EOS) of QCD at zero temperature and finite quark chemical potential under the hard-dense-loop (HDL) approximation. A comparison between the EOS under HDL approximation and the cold, perturbative EOS of QCD proposed by Fraga, Pisarski and Schaffner-Bielich is made. It is found that the pressure under HDL approximation is generally smaller than the perturbative result. In addition, we also calculate the quark number susceptibility (QNS) at finite temperature and finite chemical potential under hard-thermal/dense-loop (HTL/HDL) approximation and compare our results with the corresponding ones in the previous literature.Comment: 12 pages, 3 figure