Software-based Global Positioning System (GPS) receivers have been recognized as an effective research platform in recent years. The impact of oscillator frequency offset on hardware receiver and software receiver sig...
详细信息
Software-based Global Positioning System (GPS) receivers have been recognized as an effective research platform in recent years. The impact of oscillator frequency offset on hardware receiver and software receiver signal processing is contrasted based on a refined signal model and cross correlation function (CCF) analysis. Several online clock error correction algorithms are presented to produce unbiased measurements and clock error estimates with known and unknown front end frequency plans and with and without signal tracking and navigation solutions for single-and dual-frequency receivers on both static and dynamic platforms. The CCF formulation and the clock correction performance are validated using simulated signals and real single-and dual-frequency GPS data. The raw frequency error measurements with 0.02 s time resolution for an oven controlled crystal oscillator (OCXO) using real GPS signal report an Allan deviation (ADEV) of 1.3E-11 and a standard deviation of 1.56E-11.
Cramer-Rao bounds (CRBs) on the estimates of the main scattering center parameters, i.e., the position, intensity and geometry type, are presented in analytic forms. The resolution limit for wideband radar and the SNR...
详细信息
Cramer-Rao bounds (CRBs) on the estimates of the main scattering center parameters, i.e., the position, intensity and geometry type, are presented in analytic forms. The resolution limit for wideband radar and the SNR threshold for the correct identification of the geometry type parameter of scattering centers are further deduced. Though the results are obtained from the CRB matrix for damped exponentials;(DE) after many approximations and simplifications, their validity and adaptability for geometric theory of diffraction (GTD) based scattering center model have been verified both numerically and experimentally.
Energy efficiency and energy balance are two important issues for wireless sensor networks. In previous clustering routing algorithms, multihop transmission, sleep scheduling, and unequal clustering are always used to...
详细信息
Energy efficiency and energy balance are two important issues for wireless sensor networks. In previous clustering routing algorithms, multihop transmission, sleep scheduling, and unequal clustering are always used to improve energy efficiency and energy balance. In these algorithms, only the cluster heads share the burden of data forwarding in each round. In this paper, we propose a flow-partitioned unequal clustering routing (FPUC) algorithm to achieve better energy efficiency and energy balance. FPUC consists of two phases: clustering and routing. In the clustering phase, the competition radius is computed according to the node density and the distance from sensor nodes to the sink. The sensor nodes that have more residual energy and larger overlapping degree have higher probability to be selected as cluster heads. In the routing phase, each cluster head first finds the gateway nodes and then distributes the data flow to each of its gateway nodes depending on residual energy. After that, each gateway node forwards the data to the next hop with minimum cost. Two metrics called network lifetime and coverage lifetime are used to compare the performance of FPUC with that of the existing ones. Simulation results show that FPUC can achieve longer network lifetime and coverage lifetime than previous algorithms.
In the framework of fault reconstruction technique, this paper studies the problems of multiple mode process fault detection, fault estimation, and fault prediction systematically based on multi-PCA model. First, a mu...
详细信息
In the framework of fault reconstruction technique, this paper studies the problems of multiple mode process fault detection, fault estimation, and fault prediction systematically based on multi-PCA model. First, a multi-PCA model is used for fault detection in steady state process under different conditions, while a weighted algorithm is applied to transition process. Then, describe the faults quantitatively and use the optimization method to derive the fault amplitude under the sense of fault reconstruction. Fault amplitude drifts under different conditions even if the same fault occurs. To solve the above problem, consistent estimation algorithm of fault amplitude under different conditions has been studied. Last, employ the support vector machine (SVM) to predict the trend of the fault amplitude. Effectiveness of the algorithms proposed in this paper has been verified using Tennessee Eastman process as the study object.
In recent works several authors have considered the L-1 fidelity term, the L-2 fidelity term and the combined L-1 and L-2 fidelity term for denoising models, and they used the fast Fourier transform (FFT) algorithm wh...
详细信息
In recent works several authors have considered the L-1 fidelity term, the L-2 fidelity term and the combined L-1 and L-2 fidelity term for denoising models, and they used the fast Fourier transform (FFT) algorithm which can only use periodic boundary conditions (BCs). In this paper, we combine the augmented Lagrangian method (ALM) and the symmetric Red Black Gauss Seidel (SRBGS) method to propose three algorithms that are suitable for different BCs. Experimental results show that the proposed algorithms are effective and the model with the combined L-1 and L-2 fidelity term demonstrates more advantages in efficiency and accuracy than other models with the L-1 fidelity term or the L-2 fidelity term. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
This paper focuses on the semiglobal stabilization for a class of nonlinear systems with nonstrict feedback form. Based on a generalized scaling technique, an adaptive control algorithm with dynamic high gain is devel...
详细信息
This paper focuses on the semiglobal stabilization for a class of nonlinear systems with nonstrict feedback form. Based on a generalized scaling technique, an adaptive control algorithm with dynamic high gain is developed for a class of nonstrict feedback nonlinear systems. It can be proved that, under some appropriate design parameters, all signals of the resulting closed-loop system are bounded semiglobally, and the system state will be convergent to origin exponentially. Finally, a numerical simulation is provided to confirm the effectiveness of the proposed method.
Wireless mesh networking is an emerging technology for future broadband wireless access. Future wireless networking can benefit from a robust and reliable wire-less can less mesh backbone rendered by me routers, provi...
详细信息
Wireless mesh networking is an emerging technology for future broadband wireless access. Future wireless networking can benefit from a robust and reliable wire-less can less mesh backbone rendered by me routers, providing an all-wireless ambience. Due to the requisite multichannel communications for high-speed data transmissions, power allocation for opportunistically exploiting fading wireless channels, and packet scheduling for QoS provisioning, joint power-frequency-time resource allocation is indispensable. In this article we propose a low-complexity intracluster resource allocation algorithm, taking power allocation, subcarrier allocation, and packet scheduling into consideration. Numerical results demonstrate that our scheme is near optimal, and that our optimality-driven resource allocation approach outperforms a greedy algorithm, working out a better performance compromise among throughput, packet dropping rate, and packet delay.
It is well known that the feedforward neural networks meet numbers of difficulties in the applications because of its slow learning speed. The extreme learningmachine (ELM) is a new single hidden layer feedforward neu...
详细信息
It is well known that the feedforward neural networks meet numbers of difficulties in the applications because of its slow learning speed. The extreme learningmachine (ELM) is a new single hidden layer feedforward neural network method aiming at improving the training speed. Nowadays ELM algorithm has received wide application with its good generalization performance under fast learning speed. However, there are still several problems needed to be solved in ELM. In this paper, a new improved ELM algorithm named R-ELM is proposed to handle the multicollinear problem appearing in calculation of the ELM algorithm. The proposed algorithm is employed in bearing fault detection using stator current monitoring. Simulative results show that R-ELM algorithm has better stability and generalization performance compared with the original ELM and the other neural network methods.
This paper presents a reconstruction formula in general shift-invariant signal spaces that improve the rate of A-P iterative algorithm. We use the algorithm to show reconstruction of signals from weighted samples and ...
详细信息
This paper presents a reconstruction formula in general shift-invariant signal spaces that improve the rate of A-P iterative algorithm. We use the algorithm to show reconstruction of signals from weighted samples and also show that there is better convergence than the old one. We study the algorithm with emphasis on its implementation in field of signal processing, which the signal spaces is sufficiently large to accommodate a large number of possible models. Numerical examples results are furnished to illustrate our results. (C) 2015 Elsevier B.V. All rights reserved.
In this study, algorithms for directional relays using only current measurements are presented. Developed for radial distribution networks, these algorithms will determine fault direction based on ratios between varia...
详细信息
In this study, algorithms for directional relays using only current measurements are presented. Developed for radial distribution networks, these algorithms will determine fault direction based on ratios between variations of sequence currents during and before faults: Delta I-2/Delta I-0 ratio for line-to-ground faults and the Delta I-2/Delta I-1 ratio for line-to-line faults. The ratios are used as input of a support vector machine classifier, which was trained beforehand thanks to simulation tools. The classifier classifies ratios into two categories, according to the fault location: upstream or downstream towards the relay. Test results from simulations show good performances of the algorithms in most cases, with the presence of different distributed generation technologies. Moreover, impact of certain factors on algorithms, such as measurement errors, high-impedance faults or network reconfiguration, is studied. Finally, the implementation of algorithms is also discussed.
暂无评论