125 resultados para Error estimate.
Resumo:
Indoor wireless network based client localisation requires the use of a radio map to relate received signal strength to specific locations. However, signal strength measurements are time consuming, expensive and usually require unrestricted access to all parts of the building concerned. An obvious option for circumventing this difficulty is to estimate the radio map using a propagation model. This paper compares the effect of measured and simulated radio maps on the accuracy of two different methods of wireless network based localisation. The results presented indicate that, although the propagation model used underestimated the signal strength by up to 15 dB at certain locations, there was not a signigicant reduction in localisation performance. In general, the difference in performance between the simulated and measured radio maps was around a 30 % increase in rms error
Resumo:
In the IEEE 802.11 MAC layer protocol, there are different trade-off points between the number of nodes competing for the medium and the network capacity provided to them. There is also a trade-off between the wireless channel condition during the transmission period and the energy consumption of the nodes. Current approaches at modeling energy consumption in 802.11 based networks do not consider the influence of the channel condition on all types of frames (control and data) in the WLAN. Nor do they consider the effect on the different MAC and PHY schemes that can occur in 802.11 networks. In this paper, we investigate energy consumption corresponding to the number of competing nodes in IEEE 802.11's MAC and PHY layers in error-prone wireless channel conditions, and present a new energy consumption model. Analysis of the power consumed by each type of MAC and PHY over different bit error rates shows that the parameters in these layers play a critical role in determining the overall energy consumption of the ad-hoc network. The goal of this research is not only to compare the energy consumption using exact formulae in saturated IEEE 802.11-based DCF networks under varying numbers of competing nodes, but also, as the results show, to demonstrate that channel errors have a significant impact on the energy consumption.
Resumo:
Previous papers have noted the difficulty in obtaining neural models which are stable under simulation when trained using prediction-error-based methods. Here the differences between series-parallel and parallel identification structures for training neural models are investigated. The effect of the error surface shape on training convergence and simulation performance is analysed using a standard algorithm operating in both training modes. A combined series-parallel/parallel training scheme is proposed, aiming to provide a more effective means of obtaining accurate neural simulation models. Simulation examples show the combined scheme is advantageous in circumstances where the solution space is known or suspected to be complex. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
In this paper, we present an inertial-sensor-based monitoring system for measuring the movement of human upper limbs. Two wearable inertial sensors are placed near the wrist and elbow joints, respectively. The measurement drift in segment orientation is dramatically reduced after a Kalman filter is applied to estimate inclinations using accelerations and turning rates from gyroscopes. Using premeasured lengths of the upper and lower arms, we compute the position of the wrist and elbow joints via a proposed kinematic model. Experimental results demonstrate that this new motion capture system, in comparison to an optical motion tracker, possesses an RMS position error of less than 0.009 m, with a drift of less than 0.005 ms-1 in five daily activities. In addition, the RMS angle error is less than 3??. This indicates that the proposed approach has performed well in terms of accuracy and reliability.
Resumo:
In this paper, we propose a novel linear transmit precoding strategy for multiple-input, multiple-output (MIMO) systems employing improper signal constellations. In particular, improved zero-forcing (ZF) and minimum mean square error (MMSE) precoders are derived based on modified cost functions, and are shown to achieve a superior performance without loss of spectrum efficiency compared to the conventional linear and nonlinear precoders. The superiority of the proposed precoders over the conventional solutions are verified by both simulation and analytical results. The novel approach to precoding design is also applied to the case of an imperfect channel estimate with a known error covariance as well as to the multi-user scenario where precoding based on the nullspace of channel transmission matrix is employed to decouple multi-user channels. In both cases, the improved precoding schemes yield significant performance gain compared to the conventional counterparts.
Resumo:
In this paper, we provide experimental evidence to show that enhanced bit error rate (BER) performance is possible using a retrodirective array operating in a dynamically varying multipath environment. The operation of such a system will be compared to that obtained by a conventional nonretrodirective array. The ability of the array to recover amplitude shift keyed encoded data transmitted from a remote location whose position is not known a priori is described. In addition, its ability to retransmit data inserted at the retrodirective array back to a spatially remote beacon location whose position is also not known beforehand is also demonstrated. Comparison with an equivalent conventional fixed beam antenna array utilizing an identical radiating aperture arrangement to that of the retrodirective array are given. These show that the retrodirective array can effectively exploit the presence of time varying multipath in order to give significant reductions in BER over what can be otherwise achieved. Additionally, the retrodirective system is shown to be able to deliver low BER regardless of whether line of sight is present or absent.
Resumo:
This paper investigates the center selection of multi-output radial basis function (RBF) networks, and a multi-output fast recursive algorithm (MFRA) is proposed. This method can not only reveal the significance of each candidate center based on the reduction in the trace of the error covariance matrix, but also can estimate the network weights simultaneously using a back substitution approach. The main contribution is that the center selection procedure and the weight estimation are performed within a well-defined regression context, leading to a significantly reduced computational complexity. The efficiency of the algorithm is confirmed by a computational complexity analysis, and simulation results demonstrate its effectiveness. (C) 2010 Elsevier B.V. All rights reserved.