Wrocław University of Technology

About: Wrocław University of Technology is a education organization based out in Wrocław, Poland. It is known for research contribution in the topics: Laser & Fuzzy logic. The organization has 13115 authors who have published 31279 publications receiving 338694 citations.

Models for Heavy-tailed Asset Returns

Abstract: Many of the concepts in theoretical and empirical finance developed over the past decades – including the classical portfolio theory, the Black-Scholes-Merton option pricing model or the RiskMetrics variance-covariance approach to Value at Risk (VaR) – rest upon the assumption that asset returns follow a normal distribution. But this assumption is not justified by empirical data! Rather, the empirical observations exhibit excess kurtosis, more colloquially known as fat tails or heavy tails (Guillaume et al., 1997; Rachev and Mittnik, 2000). The contrast with the Gaussian law can be striking, as in Figure 1.1 where we illustrate this phenomenon using a ten-year history of the Dow Jones Industrial Average (DJIA) index.

Methods of Sensors Localization in Wireless Sensor Networks

Abstract: In recent years there has been a growing interest in wireless sensor networks (WSN) applications. Such sensor networks can be used to control temperature, humidity, contamination, pollution etc. Self-organization and routing algorithms dedicated to wireless sensor networks usually assume that sensors absolute positions are unknown and all decisions are based on sensor's own local information. This assumption makes wireless sensor networks more flexible and energy conserve because making decisions locally is faster and energy efficient. But sooner or later sensors positions have to be found (when sensor sends a message about some event we of course would like to know where this event takes place). In this paper we describe different solutions of finding transceivers positions in wireless networks and we discuss localization in wireless sensor networks. We propose to transfer localization function from base stations to every sensor. We evaluate presented method using simulations

Optimization of fuzzy-logic speed controller for DC drive system with elastic joints

Abstract: This paper deals with the analysis of a DC drive system with elastic joints and different speed controllers. The control structure with one and two speed feedbacks was analyzed. The dynamics of the drive system with classical proportional-integral (PI) and fuzzy-logic (FL) speed controllers was compared. Parameters of the classical PI and FL speed controllers were optimized using the same control indexes. Controllers were parameterised using the hybrid genetic-gradient algorithm. The simulation results for different parameters and operation modes of the drive system were demonstrated and compared.