Dynamical model of sequential spatial memory: winnerless competition of patterns

We introduce a new biologically-motivated model of sequential spatial memory which is based on the principle of winnerless competition (WLC). We implement this mechanism in a two-layer neural network structure and present the learning dynamics which leads to the formation of a WLC network. After learning, the system is capable of associative retrieval of pre-recorded sequences of spatial patterns.Comment: 4 pages, submitted to PR

Product-Group Unification in Type IIB String Thoery

The product-group unification is a model of unified theories, in which masslessness of the two Higgs doublets and absence of dimension-five proton decay are guaranteed by a symmetry. It is based on SU(5) x U(N) (N=2,3) gauge group. It is known that various features of the model are explained naturally, when it is embedded in a brane world. This article describes an idea of how to accommodate all the particles of the model in Type IIB brane world. The GUT-breaking sector is realized by a D3--D7 system, and chiral quarks and leptons arise from intersection of D7-branes. The D-brane configuration can be a geometric realization of the non-parallel family structure of quarks and leptons, an idea proposed to explain the large mixing angles observed in the neutrino oscillation. The tri-linear interaction of the next-to-minimal supersymmetric standard model is obtained naturally in some cases.Comment: 33 pages, 5 figure

Evolutionary algorithms for real-world instances of the automatic frequency planning problem in GSM networks

Abstract. Frequency assignment is a well-known problem in Operations Research for which different mathematical models exist depending on the application specific conditions. However, most of these models are far from considering actual technologies currently deployed in GSM networks (e.g. frequency hopping). These technologies allow the network capacity to be actually increased to some extent by avoiding the interferences provoked by channel reuse due to the limited available radio spectrum, thus improving the Quality of Service (QoS) for subscribers and an income for the operators as well. Therefore, the automatic generation of frequency plans in real GSM networks is of great importance for present GSM operators. This is known as the Automatic Frequency Planning (AFP) problem. In this paper, we focus on solving this problem for a realistic-sized, real-world GSM network by using Evolutionary Algorithms (EAs). To be precise, we have developed a (1, λ) EA for which very specialized operators have been proposed and analyzed. Results show that this algorithmic approach is able to compute accurate frequency plans for real-world instances.