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For complex large scale networks, like social networks, it is typically impossible to observe complete information about their topology structure or link weight directly. A recent proposal, the network resonance method, can estimate the eigenvalues and eigenvectors of the Laplacian matrix for representing network structure, by using the resonance phenomena of oscillation dynamics on networks. However,...
For the large-scale wireless mobile networks, the topology or global state information directly affects congestion control, traffic control, quality of service and so on. Due to the dynamic change of the opportunistic network structure, the node can not perceive the current state of the network, therefore, it is important to improve the routing quality by designing a topology aware algorithm that...
This paper proposes a method for speeding up the estimation of the absolute value of largest eigenvalue of an asymmetric tridiagonal matrix based on Power method. An error analysis shows that the proposed method provide errors no greater than the usual Power method. The proposed method involves the computation of the tridiagonal matrix square under analysis, which is performed through a proposed fast...
In Recent years, manifold learning has become an important research direction in the field of machine learning and pattern recognition. As an effective way of representation embedded in low-dimensional space of high-dimensional data, the manifold learning algorithm, which is based on the spectral theory, has been widely used. This paper presents an estimation algorithm of Laplacian Eigenvalues and...
In this paper, a new direction of arrival (DOA) estimation method is proposed for uniform linear array when both uncorrelated and coherent sources are present. After the first eigen decomposition of the received data covariance matrix, the eigenvector corresponding to the maximum eigenvalue is used to construct a new matrix, by the second eigen decomposition of which, the DOAs of the uncorrelated...
This paper presents a modified parameter tuning approach that enables a better quantitative analysis of the nonlinear dynamics of long term arterial blood pressure regulation. A previously developed nonlinear model of blood pressure regulation is linearized about its equilibrium point. Instead of any traditional fixed parameter approach this linearized version utilizes multiple model approach. Fractional...
The low-rank structure reverberation suppression algorithm is a better method to restrain the sea interface reverberation. But the data processing speed of the method is very slowly due to the complexity of singular value decomposition. It can not meet the real-time requirement in actual application. This article present a signal subspace fast approximation method based on unitary transformation which...
Blind source separation algorithm is usually not able to estimate the number of unknown signal sources. In many occasions, the number of source signal is unknown and may even be in dynamic changes. This paper has achieved to estimate the number of sources and real-time tracking using subspace method in the over-determined blind source separation, while the number of sources is unknown and dynamic...
A new algorithm which can detect the number of sources accurately in the case of a high degree of coherence and small difference between incident angles is proposed in this paper. The algorithm is based on the criterion of eigenvalue transformation of the covariance Matrix. Firstly, the output covariance matrix is decohered with toeplitz matrix, and then the number of coherent sources is estimated...
In this paper we apply the diffusion framework to dense optical flow estimation. Local image information is represented by matrices of gradients between paired locations. Diffusion distances are modelled as sums of eigenvectors weighted by their eigenvalues extracted following the eigen decomposion of these matrices. Local optical flow is estimated by correlating diffusion distances characterizing...
In this paper, an effective joint direction-of-arrival (DOA) and propagation delay estimation method is proposed for multipath signals impinging the uniform linear antenna array. In this presented method, the real and imaginary parts of the ith eigenvalue of a matrix are one-to-one related to the DOA and propagation delay of the ith path's signal. Thus, the paring of the estimated DOAs and delays...
A new method based on fourth-order cumulant for the joint estimation of the range and DOA of spatial near-field sources is presented. The proposed method adopts the non-centro-symmetric array, and constructs three cumulant matrixes using received array data; the aperture loss is effectively avoided. The method estimates the DOA and range parameters by the tripartite relationships among subspace matrixes,...
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