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This paper presents a novel approach to estimate chirp parameters in case of strong interference between two or more components in a 1D signal. In particular, it will proved that non ridge points provide a more robust parameters estimation in case of critical conditions. The proposed method has been tested on some synthetic signals and preliminary experimental results are very promising.
The paper considers a new method of the Quality of Service (QoS) assurance in opportunistic access to wireless networks using a game theoretic-framework. The perfect full information of the involved links is made known to the central management unit called spectrum broker. Three algorithms of spectrum sharing are proposed. In each algorithm, Cournot oligopoly competition or monopolistic behaviour...
Effective sensor scheduling requires the consideration of long-term effects and thus optimization over long time horizons. Determining the optimal sensor schedule, however, is equivalent to solving a binary integer program, which is computationally demanding for long time horizons and many sensors. For linear Gaussian systems, two efficient multi-step sensor scheduling approaches are proposed in this...
The information flow through a radar system channel is studied for various component design choices including the radar measurement function, signature feature selection, and classifier decision rule. A simplified target scattering model is used to analyze the application of the information theoretical channel model.
Cognitive radio terminals sense the spectrum to detect temporarily unoccupied spectrum gaps and transmit. The behavior of a network of cognitive radio terminals therefore depends on the spectrum occupancy perceived by each terminal at its local environment. In this context, this work explores (via empirical measurements) the spectrum occupancy that would be perceived by a cognitive radio terminal...
In many real world data applications, objects may have missing attributes. Conventional techniques used to classify this kind of data are represented in a feature space. However, usually they need imputation methods and/or changing the classifiers. In this paper, we propose two classification alternatives based on dissimilarities. These techniques promise to be appealing for solving the problem of...
A new and effective approach for mental fatigue analysis is presented here. Empirical mode decomposition (EMD), as a fully adaptive and data-driven method for analyzing nonlinear and nonstationary time series, is presented for measuring the synchronization of the brain rhythms from different brain lobes. The EMD algorithm is applied to a desired channel and each time one of the extracted intrinsic...
In this paper we deal with the problem of user-driven Call Admission Control for Voice over IP communications in a Wireless LAN environment. We argue that state-of-the-art solutions to this problem are suboptimal, since they leverage on analytical models whose assumptions are not necessarily verified in the scenario considered. To overcome this problem, we propose a cognitive solution based on Multilayer...
Information geometry is a new and increasing topic between statistics, estimation and differential geometry. Many amazing relationships between these domains were established through the last years. Unfortunately, it is not easy to find an easy approach to information geometry, which requires a deep understanding of differential geometry and statistics. The paper presents an easy readable introduction...
This article describes a graphical approach for multi-standards SDR design formalization. An SDR consists of software components whose behavior can be changed by reconfiguration procedure. In a common operator design this change requires only an adjustment of certain parameters. The optimal way of realizing a multi-standards terminal is to identify the common functions and operators between standards...
Tracking the spread of an epidemic disease like seasonal or pandemic influenza is an important task that can reduce its impact and help authorities plan their response. In particular, early detection and geolocation of an outbreak are important aspects of this monitoring activity. Various methods are routinely employed for this monitoring, such as counting the consultation rates of general practitioners...
We address the task of detecting surprising patterns in large textual data streams. These can reveal events in the real world when the data streams are generated by online news media, emails, Twitter feeds, movie subtitles, scientific publications, and more. The volume of interest in such text streams often exceeds human capacity for analysis, such that automatic pattern recognition tools are indispensable...
Recent research show that utilization of knowledge of the environment can allow a radar system to adapt its processing to improve its performance. Furthermore, a radar system that utilize both a-priori and measured knowledge in an adaptive close loop manner could seem to be cognitive of its environment, able to adapt to changes to optimize performance. Reinforced learning could play a vital role as...
The objective of this paper is to develop methods for enhanced clutter/interference suppression by redesigning the transmit pattern in the spatio-temporal domain to emphasize the target response and de-emphasize the clutter response. In this context, traditional adaptive transmitter weight design in the spatial domain to generate multiple spatial nulls is extended to both the spatio-temporal domains...
In recent years a number of organizations, both national and international, have put significant efforts in developing knowledge-based integrated maritime surveillance (IMS) systems. The final aim is to have a clear picture of the position, classification, identification and movement of cooperative and non-cooperative targets entering and leaving the 200 nautical miles limit of the Exclusive Economic...
An airborne ground looking radar sensor's performance may be enhanced by selecting algorithms adaptively as the environment changes. A short description of an airborne intelligent radar system (AIRS) is presented with an in-depth description of the knowledge based filter and detection portions. A second level of artificial intelligence (AI) processing is presented that monitors, tests, and learns...
We consider a network of cognitive radios (CRs) where each CR obtains noisy multivariate measurements of the quality of several logical channels and needs to decide which channel to access. Assuming the CRs are rational devices, each CR determines which channel to access, based on its expected throughput and Bayesian estimate of the intention of other CRs. We formulate conditions for which the Bayesian...
Command and control applications are important especially in tactical scenarios. For such scenarios wireless multi-hop networks may be deployed as they can be used even when there is no infrastructure left. Due to the specific characteristics of these networks the problem of Out-of-Sequence (OoS) measurements for tracking applications arises. In this paper, we present an exhaustive, realistic evaluation...
We investigate three extensions to the generative similarity-based classifier called local similarity discriminant analysis (local SDA): a Bayesian approach to estimating the pmfs based on the assumption that similarities are multinomially distributed and on the Dirichlet prior distribution; a pairwise-similarity formulation of local SDA that accounts for all local pairwise similarities to estimate...
The paper proposes a new variational Bayesian algorithm for multivariate regression with attribute-distributed or dimensionally distributed data. Compared to the existing approaches the proposed algorithm exploits the variational version of the Space-Alternating Generalized Expectation-Maximization (SAGE) algorithm that by means of admissible hidden data - an analog of the complete data in the EM...
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