A stationary two-component markovian process (Xn; Sn)n>1 is considered with the first component observable and the second one non-observable. The problem of filtering a stochastic signal (Sn)n>1 from the mixture with a noise by observations Xn 1 = X1; ¢ ¢ ¢ ;Xn is solved in non-parametric uncertainty regarding the distribution of the desired signal. This means that the probabilistic parametric model of the useful signal (Sn) is assumed to be completely unknown. Under these assumptions, in general, it is impossible to build an optimal Bayesian estimator. However, for a more restricted class of observation models, in which the conditional density f(xnjsn; xn¡1 1 ) belongs to conditionally- exponential family of distribution densities, the Bayesian estimator is a solution of some nonrecurrent equation which depends only on probabilistic characteristics of the observable process (Xn). These unknown characteristics can be restored from observations Xn 1 by using stable non-parametric estimation procedures adapted to dependent data. In detail the nonlinear multiplicative observation model with non-Gaussian noise is considered, and the non-parametric estimator of an unknown gain coefficient is constructed. The results of the model experiment show that the quality of the non-parametric estimator, built for nonlinear observation model, is slightly worse than the quality of the Bayesian estimator (which is naturall), but better than the quality of optimal linear estimator. When building a stable nonparametric procedures the choice of smoothing and regularization parameters plays the crucial role. We propose the optimal choice of these parameters, which leads to an automatic algorithm of non-parametric filtering.

This paper studies models of centralized, decentralized and distributed control of excitation in a network of interacting purposeful agents. As examples, we analyze models of threshold behavior and mob control.

We study the action of semisimple Lie group G on homgeneous bundle over flag manifold G/H. We find field of differential invariants of this action on the module of holomorphic sections and obtain the criterion of G-equivalence of two non-degenerated sections.

This book focuses on organization and mechanisms of expert decision-making support using modern information and communication technologies, as well as information analysis and collective intelligence technologies (electronic expertise or simply e-expertise). Chapter 1 (E-Expertise) discusses the role of e-expertise in decision-making processes. The procedures of e-expertise are classified, their benefits and shortcomings are identified, and the efficiency conditions are considered. Chapter 2 (Expert Technologies and Principles) provides a comprehensive overview of modern expert technologies. A special emphasis is placed on the specifics of e-expertise. Moreover, the authors study the feasibility and reasonability of employing well-known methods and approaches in e-expertise. Chapter 3 (E-Expertise: Organization and Technologies) describes some examples of up-to-date technologies to perform e-expertise. Chapter 4 (Trust Networks and Competence Networks) deals with the problems of expert finding and grouping by information and communication technologies. Chapter 5 (Active Expertise) treats the problem of expertise stability against any strategic manipulation by experts or coordinators pursuing individual goals. The book addresses a wide range of readers interested in management, decision-making and expert activity in political, economic, social and industrial spheres.

This book contains the proceedings of the 17th International Conference on Distributed Computer and Communication Networks (DCCN 2013). The conference is a continuation of traditional international conferences of the DCCN series, which took place in Bulgaria (Sofia, 1995, 2005, 2006, 2008, 2009), Israel (Tel Aviv, 1996, 1997, 1999, 2001), and Russia (Moscow, 1998, 2000, 2003, 2007, 2010, 2011) in the last 16 years. The main idea of the conference is to assemble researchers from various countries working in the area of theory and applications of distributed computer and communication networks, to exchange the expertise, and to discuss the perspectives of development and collaboration in this area. The content of this volume is related to the following subjects: 1. Computer and communication networks architecture optimization 2. Control in computer and communication networks 3. Performance and QoS evaluation in wireless networks 4. Modeling and simulation of network protocols 5. Queueing theory 6. Wireless IEEE 802.11, IEEE 802.15, IEEE 802.16 and UMTS (LTE) networks 7. FRID technology and its application in intellectual transportation networks 8. Protocols design (MAC, Routing) for centimeter and millimeter wave mesh networks 9. Internet and Web applications and services 10. Application integration in distributed information systems