АСИМПТОТИЧЕСКОЕ ПОВЕДЕНИЕ РЕЗИСТОРНЫХ РАССТОЯНИЙ В ГРАФАХ КЭЛИ

In the present paper, we prove asymptotically exact bounds for resistance distances in families of Cayley graphs that either have a girth of more than 4 or are free of subgraphs K2,t, assuming that the growth function is at least subexponential, and either the diameter or the inverse value of the spectral gap are polynomial with respect to degrees of a graph.В настоящей работе доказаны асимптотически точные оценки для резисторных расстояний в некоторых семействах графов Кэли при условии, что функция роста является как минимум субэкспоненциальной, а диаметр либо обратная величина к спектральному пробелу полиномиальны по степени графа. 

Some applications of noncommutative groups and semigroups to information security

We present evidence why the Burnside groups of exponent 3 could be a good candidate for a platform group for the HKKS semidirect product key exchange protocol. We also explore hashing with matrices over SL2(Fp), and compute bounds on the girth of the Cayley graph of the subgroup of SL2(Fp) for specific generators A, B. We demonstrate that even without optimization, these hashes have comparable performance to hashes in the SHA family

Distance-regular graphs

This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN' [Brouwer, A.E., Cohen, A.M., Neumaier, A., Distance-Regular Graphs, Springer-Verlag, Berlin, 1989] was written.Comment: 156 page

Аналог теоремы Альдуса о времени перемешивания для групп комплексных отражений

The subject of this paper is the mixing time of random walks on minimal Cayley graphs of complex reflection groups G(m,1,n). The key role in estimating it is played by the coupling of distributions, which has been used before for the same task on symmetric groups. The difficulty with its adaptation for the current case is that there are now two components in a walk, which are to be coupled, and they influence each other’s behaviour. To solve this problem, random walks are split into several blocks for each of which the time needed for their states to match is estimated separately. The result is upper and lower bounds on mixing times of random walks on complex reflection groups, analogous to those obtained by Aldous for a symmetric group.Исследуется время перемешивания случайных блужданий на минимальных графах Кэли групп комплексных отражений G(m,1,n). Ключевую роль при этом играет адаптация метода склеивания распределений, применявшегося ранее для симметрической группы. Сложность адаптации заключается в том, что с обобщением в случайном блуждании появляются две компоненты, к которым нужно применять склеивание, и эти компоненты влияют на обоюдное поведение. Для решения этой проблемы случайные блуждания разбиваются на несколько бло- ков, для каждого из которых даются отдельные оценки времени, необходимого для совпадения состояний. Доказаны оценки сверху и снизу на время перемешивания случайных блужданий на группах комплексных отражений, аналогичные оценкам Альдуса для симметрической группы

Localization and Optimization Problems for Camera Networks

In the framework of networked control systems, we focus on networks of autonomous PTZ cameras. A large set of cameras communicating each other through a network is a widely used architecture in application areas like video surveillance, tracking and motion. First, we consider relative localization in sensor networks, and we tackle the issue of investigating the error propagation, in terms of the mean error on each component of the optimal estimator of the position vector. The relative error is computed as a function of the eigenvalues of the network: using this formula and focusing on an exemplary class of networks (the Abelian Cayley networks), we study the role of the network topology and the dimension of the networks in the error characterization. Second, in a network of cameras one of the most crucial problems is calibration. For each camera this consists in understanding what is its position and orientation with respect to a global common reference frame. Well-known methods in computer vision permit to obtain relative positions and orientations of pairs of cameras whose sensing regions overlap. The aim is to propose an algorithm that, from these noisy input data makes the cameras complete the calibration task autonomously, in a distributed fashion. We focus on the planar case, formulating an optimization problem over the manifold SO(2). We propose synchronous deterministic and distributed algorithms that calibrate planar networks exploiting the cycle structure of the underlying communication graph. Performance analysis and numerical experiments are shown. Third, we propose a gossip-like randomized calibration algorithm, whose probabilistic convergence and numerical studies are provided. Forth and finally, we design surveillance trajectories for a network of calibrated autonomous cameras to detect intruders in an environment, through a continuous graph partitioning problem