An energy-efficient opportunistic collaborative beamformer with one-bit feedback is proposed for ad hoc sensor networks over Rayleigh fading channels. In contrast to conventional collaborative beamforming schemes in w...
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An energy-efficient opportunistic collaborative beamformer with one-bit feedback is proposed for ad hoc sensor networks over Rayleigh fading channels. In contrast to conventional collaborative beamforming schemes in which each source node uses channel state information to correct its local carrier offset and channel phase, the proposed beamforming scheme opportunistically selects a subset of source nodes whose received signals combine in a quasi-coherent manner at the intended receiver. No local phase-precompensation is performed by the nodes in the opportunistic collaborative beamformer. As a result, each node requires only one bit of feedback from the destination in order to determine if it should or should not participate in the collaborative beamformer. Analytical results show that the received signal power obtained with the proposed beamforming scheme scales linearly with the number of available source nodes. Since the optimal node selection rule requires an exhaustive search over all possible subsets of source nodes, two low-complexity selection algorithms are developed. Simulation results confirm the effectiveness of opportunistic collaborative beamforming with the low-complexity selection algorithms.
The purpose of this paper is to investigate the iterative algorithm for finding approximate solutions of a class of mixed variational-like inequalities in a real Hilbert space, where the iterative algorithm is present...
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The purpose of this paper is to investigate the iterative algorithm for finding approximate solutions of a class of mixed variational-like inequalities in a real Hilbert space, where the iterative algorithm is presented by virtue of the auxiliary principle technique. On one hand, the existence of approximate solutions of this class of mixed variational-like inequalities is proven. On the other hand, it is shown that the approximate solutions converge strongly to the exact solution of this class of mixed variational-like inequalities.
作者：
Bian HailongChen GuangjuCAT Lab
School of Automation Engineering Univ. of Electronic Science and Technology Chengdu 610054 P. R. China
To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform (STFT) is brought forward. Fi...
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To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform (STFT) is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.
作者：
Sun, YijunUniv Florida
Interdisciplinary Ctr Biotechnol Res Gainesville FL 32610 USA
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform significantly better than RELIEF, with...
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RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform significantly better than RELIEF, without introducing a large increase in computational complexity. Our work starts from a mathematical interpretation of the seemingly heuristic RELIEF algorithm as an online method solving a convex optimization problem with a margin-based objective function. This interpretation explains the success of RELIEF in real application and enables us to identify and address its following weaknesses. RELIEF makes an implicit assumption that the nearest neighbors found in the original feature space are the ones in the weighted space and RELIEF lacks a mechanism to deal with outlier data. We propose an iterative RELIEF (I-RELIEF) algorithm to alleviate the deficiencies of RELIEF by exploring the framework of the Expectation-Maximization algorithm. We extend I-RELIEF to multiclass settings by using a new multiclass margin definition. To reduce computational costs, an online learning algorithm is also developed. Convergence analysis of the proposed algorithms is presented. The results of large-scale experiments on the UCI and microarray data sets are reported, which demonstrate the effectiveness of the proposed algorithms, and verify the presented theoretical results.
Matrix iterative algorithms are proposed for solving the matrix least square problem of BXA(T) = F with variant linear constraints on solutions such as symmetry, skew-symmetry, and symmetry/skew-symmetry commuting wit...
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Matrix iterative algorithms are proposed for solving the matrix least square problem of BXA(T) = F with variant linear constraints on solutions such as symmetry, skew-symmetry, and symmetry/skew-symmetry commuting with a given symmetric matrix P. We characterize the linear mapping from the constrained solution sets to their (independent) parameter spaces, and use these properties to deduce the matrix iterations, based on the classical algorithm LSQR for solving (unconstrained) LS problem. Numerical results are reported that show the efficiency of the proposed methods. (c) 2006 Elsevier Inc. All rights reserved.
In this paper, we introduce a new class of operator-general H-monotone operators in Banach space. We define a proximal mapping associated with the general H-monotone operator and show its Lipschitz continuity. We also...
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In this paper, we introduce a new class of operator-general H-monotone operators in Banach space. We define a proximal mapping associated with the general H-monotone operator and show its Lipschitz continuity. We also consider a new class of variational inclusions involving these general H-monotone operators and constructed a new iterative algorithm for solving the variational inclusion in Banach spaces. Under some suitable conditions, we prove the convergence of the iterative sequence generated by the algorithm. (C) 2007 Elsevier Ltd. All rights reserved.
A novel iterative algorithm for estimating the frequency of a single complex sinusoid in the complex white Gaussian noise is proposed. Inspired by the works of Fitz, L&R, and the ILP approaches, the algorithm is b...
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A novel iterative algorithm for estimating the frequency of a single complex sinusoid in the complex white Gaussian noise is proposed. Inspired by the works of Fitz, L&R, and the ILP approaches, the algorithm is based on the repeated use of an autocorrelation-based frequency estimator. This approach is different from the iterative linear prediction (ILP) algorithm, yet produces very comparable performance. Like the ILP algorithm, the proposed estimator has the reduced threshold, and its performance is close to that of the ML estimation and uniform across the frequency range of -pi to pi. In addition, the proposed estimator demonstrates an asymptotic error variance of 0.14 dB above the CRB for N = 1024 and 0.62 dB for N = 48, which is better than that of the ILP algorithm. (c) 2006 Elsevier B.V. All rights reserved.
Schematic networks are linear abstractions of functional networks, such as route networks. Lines in the original network are modified in order to produce a schematic network which satisfies a set of constraints chosen...
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Schematic networks are linear abstractions of functional networks, such as route networks. Lines in the original network are modified in order to produce a schematic network which satisfies a set of constraints chosen to design the network. A method is described which accomplishes this line transformation using an iterative improvement technique driven by design constraints. The method maintains topological characteristics of the network by the use of simple geometric operations and tests. The iterative process can be repeated until the line displacements become small enough or until it meets user defined stopping criteria. Experimental results are provided to examine the acceptability of outcomes and the convergence of the applied iterative technique. Criteria for measuring the quality of results, as well as for stopping the iterative approach are presented.
The paper presents quality of service (QoS) optimisation strategy for multi-criteria scheduling on the grid, based on a mathematical QoS model and a distributed iterative algorithm. Three QoS criteria are considered, ...
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The paper presents quality of service (QoS) optimisation strategy for multi-criteria scheduling on the grid, based on a mathematical QoS model and a distributed iterative algorithm. Three QoS criteria are considered, namely payment, deadline and reliability, which are formulated as utility function. The optimisation problem is split into two parts: task optimisation performed on behalf of the user and resource optimisation performed on behalf of the grid. The strategy employs three types of agents: task agents responsible for task optimisation, computation resource and network resource agents responsible for resource optimisation. The agents apply economic models for optimisation purposes. Dynamic programming is used to optimise the total system utility function in terms of an iterative algorithm. The objective of multi-criteria scheduling is to maximise the global utility of the system. This paper proposes an iterative scheduling algorithm that is used to perform QoS optimisation-based multi-criteria scheduling. The proposed QoS optimisation-based multi-criteria scheduling problem solution has been practically examined by simulation experiments. (C) 2006 Elsevier Inc. All rights reserved.
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