We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (...
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We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (MAB) approach to solve the problem of SUs with network coding under unknown channel quality in CRNs. We analytically prove the asymptotical-throughput optimality of the proposed two-dimensional MAB algorithm. Simulation results show that our proposed algorithm achieves comparable throughput performance, compared to both the theoretical upper bound and the scheme assuming known channel quality information.
Real-time structural identification and damage detection are necessary for on-line structural damage detection and optimal structural vibration control during severe loadings. Frequently, structural damage can be refl...
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Real-time structural identification and damage detection are necessary for on-line structural damage detection and optimal structural vibration control during severe loadings. Frequently, structural damage can be reflected in the stiffness degradation of structural elements. In this article, a time-domain three-stage algorithm with computational efficiency is proposed for real-time tracking the onsets, locations, and extents of abrupt stiffness degradations of structural elements using measurements of structural acceleration responses. Structural dynamic parameters before damage are recursively estimated in stage I. Then, the time instants and possible locations of degraded structural elements are detected by tracking the errors between the measured data and the corresponding estimated values in stage II. Finally, the exact locations and extents of stiffness degradations of structural elements are determined by solving simple constrained optimization problems in stage III. Both numerical examples and an experimental test are used to validate the proposed algorithm for real-time tracking the abrupt stiffness degradations of structural elements in linear or nonlinear structures using measurements of structural acceleration responses polluted by noises.
This work proposes an improved unscented Kalman filter (UKF)-based simultaneous localization and mapping (SLAM) algorithm based on an adaptive unscented Kalman filter (AUKF) with a noise statistic estimator. The algor...
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This work proposes an improved unscented Kalman filter (UKF)-based simultaneous localization and mapping (SLAM) algorithm based on an adaptive unscented Kalman filter (AUKF) with a noise statistic estimator. The algorithm solves the issue that conventional UKF-SLAM algorithms have declining accuracy, with divergence occurring when the prior noise statistic is unknown and time-varying. The new SLAM algorithm performs an online estimation of the statistical parameters of unknown system noise by introducing a modified Sage-Husa noise statistic estimator. The algorithm also judges whether the filter is divergent and restrains potential filtering divergence using a covariance matching method. This approach reduces state estimation error, effectively improving navigation accuracy of the SLAM system. A line feature extraction is implemented through a Hough transform based on the ranging sonar model. Test results based on unmanned underwater vehicle (UUV) sea trial data indicate that the proposed AUKF-SLAM algorithm is valid and feasible and provides better accuracy than the standard UKF-SLAM system.
Recently the one-counter trace languages and the context-free trace languages have been characterized through restricted types of cooperating distributed systems (CD-systems) of stateless deterministic restarting auto...
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Recently the one-counter trace languages and the context-free trace languages have been characterized through restricted types of cooperating distributed systems (CD-systems) of stateless deterministic restarting automata with window size one (so-called stl-det-R(1)-automata) that work in mode '=1' and that use an external counter or pushdown store to determine the successor components within computations. Here we study the deterministic variants of these CD-systems, comparing the resulting language classes to the classes of languages defined by CD-systems of stl-det-R(1)-automata without such an external device and to some classical language families, among them in particular the classes of rational, one-counter, and context-free trace languages. In addition, we present a large number of (non-)closure properties for our language classes.
A procedure for approximating fractional-order systems by means of integer-order state-space models is presented. It is based on the rational approximation of fractional-order operators suggested by Oustaloup. First, ...
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A procedure for approximating fractional-order systems by means of integer-order state-space models is presented. It is based on the rational approximation of fractional-order operators suggested by Oustaloup. First, a matrix differential equation is obtained from the original fractional-order representation. Then, this equation is realized in a state-space form that has a sparse block-companion structure. The dimension of the resulting integer-order model can be reduced using an efficient algorithm for rational L-2 approximation. Two numerical examples are worked out to show the performance of the suggested technique. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Robot simultaneous localization and mapping (SLAM) problem is a very important and challenging issue in the robotic field. The main tasks of SLAM include how to reduce the localization error and the estimated error of...
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Robot simultaneous localization and mapping (SLAM) problem is a very important and challenging issue in the robotic field. The main tasks of SLAM include how to reduce the localization error and the estimated error of the landmarks and improve the robustness and accuracy of the algorithms. The extended Kalman filter (EKF) based method is one of the most popular methods for SLAM. However, the accuracy of the EKF based SLAM algorithm will be reduced when the noise model is inaccurate. To solve this problem, a novel bioinspired neural model based SLAM approach is proposed in this paper. In the proposed approach, an adaptive EKF based SLAM structure is proposed, and a bioinspired neural model is used to adjust the weights of system noise and observation noise adaptively, which can guarantee the stability of the filter and the accuracy of the SLAM algorithm. The proposed approach can deal with the SLAM problem in various situations, for example, the noise is in abnormal conditions. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach.
In this paper, a robust and blind watermarking scheme for three dimensional (3-D) anaglyph images is proposed. Since the computational cost of Red-Green-Blue (RGB) processing is quite high, we have used 3-D Discrete W...
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In this paper, a robust and blind watermarking scheme for three dimensional (3-D) anaglyph images is proposed. Since the computational cost of Red-Green-Blue (RGB) processing is quite high, we have used 3-D Discrete Wavelet Transform (3-D DWT) to decompose the image and process it directly. The watermark to be embedded is computed from the image and also the process involves watermark strength factor which scales the quality of the watermark. Jacket matrix is used due to its simplicity in the watermark embedding and extraction processes. Experimental results show that the proposed scheme is highly imperceptible and robust against various image processing and signal processing attacks. Comparisons with the state-of-the-art demonstrate the effectiveness of our scheme. (C) 2013 Elsevier Ltd. All rights reserved.
The problem of texture mapping on real world objects has attracted attention(11,8) recently. A work by Lensch et al.(9) addressed the problem of locating a camera position in the celestial sphere and then mapping the ...
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The problem of texture mapping on real world objects has attracted attention(11,8) recently. A work by Lensch et al.(9) addressed the problem of locating a camera position in the celestial sphere and then mapping the acquired pictures on a real world object. The entire process took a half hour to one hour to map 10 to 15 pictures. In this paper we propose a new innovative algorithm to speed up the texture mapping or painting process in real-time. We built a PC-based system using a commonly available video card with a geometry engine. Mapping of a picture required about 20 seconds. It is successful in giving an illusion to the operator to paint a colorless real world object with a color texture brush.
The transmission control protocol (TCP) has contributed to the tremendous success of the Internet but it also faces many challenges which are becoming more and more significant as the network grows. Although numerous ...
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The transmission control protocol (TCP) has contributed to the tremendous success of the Internet but it also faces many challenges which are becoming more and more significant as the network grows. Although numerous congestion control algorithms have been proposed to improve the performance of TCP in heterogeneous networks, designing a congestion control algorithm that could achieve high utilisation, ensure fairness and maintain stability remains a great challenge. A novel congestion control algorithm named fair TCP (FTCP) has been proposed to mitigate these challenges. FTCP mitigates these challenges through the following strategies: First, increase the round trip time (RTT)-fairness by altering TCP's initial congestion control window (cwnd) and adjusting the cwnd's growth rate to make FTCP flows with different RTTs achieve the same throughput. Secondly, balance the transmission efficiency and TCP-friendliness by dynamically adjusting the aggressiveness of FTCP according to the congestion level of the link. Preliminary experimental evaluations verify that FTCP has obvious advantages in transmission efficiency, RTT-fairness and TCP-friendliness comparing to the state-of-the-art congestion control algorithms.
This paper presents an algorithm for optimization of programs at the compilation stage that analyzes execution of various program segments at available processor frequencies and selects an energy-effective schedule of...
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This paper presents an algorithm for optimization of programs at the compilation stage that analyzes execution of various program segments at available processor frequencies and selects an energy-effective schedule of frequencies with regard to the constraints of the arising additional time of operation. This algorithm is complemented by an operating-system manager that controls setting of a desired processor mode and resolves conflicts in multi-program environment.
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