iterative algorithms for finding two-sided approximations to the eigenvalues of nonlinear algebraic eigenvalue problems are examined. These algorithms use an efficient numerical procedure for calculating the first and...
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Heat transfer processes in goffered heat sink are investigated. Dependences of heat transfer factors from an angle of goffering are received. The optimization opportunities of weight and sizes are shown.
ISBN:
(纸本)9789665335870
Heat transfer processes in goffered heat sink are investigated. Dependences of heat transfer factors from an angle of goffering are received. The optimization opportunities of weight and sizes are shown.
In this paper an iterative Least Square (LS) channel estimation algorithm for MIMO OFDM systems is proposed. Compared with the common LS channel estimation, this algorithm can highly improve the estimation accuracy. M...
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ISBN:
(纸本)0780379381
In this paper an iterative Least Square (LS) channel estimation algorithm for MIMO OFDM systems is proposed. Compared with the common LS channel estimation, this algorithm can highly improve the estimation accuracy. Moreover, the lowpass filtering in the time domain reduces AWGN and ICI significantly. This algorithm enables MIMO OFDM systems to work well in mobile situations. simulation results confirmed good MSE performance of this algorithm.
The auxiliary principle technique is extended to study a class of generalized set-valued strongly nonlinear mixed variational-like type inequalities. Firstly, the existence of solutions to the auxiliary problems for t...
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The auxiliary principle technique is extended to study a class of generalized set-valued strongly nonlinear mixed variational-like type inequalities. Firstly, the existence of solutions to the auxiliary problems for this class of generalized set-valued strongly nonlinear mixed variational-like type inequalities is shown. Secondly, the iterative algorithm for solving this class of generalized set-valued strongly nonlinear mixed variational-like type inequalities is given by using this existence result. Finally,the strong convergence of iterative sequences generated by the algorithm is proven. The present results improve,generalize and modify the earlier and recent ones obtained previously by some authors in the literature.
The classical Gerchberg-Saxton algorithm is introduced into the image recovery in fractional Fourier domain after adaptation. When this algorithm is applied directly, its performance is good for smoothed image, but ba...
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The classical Gerchberg-Saxton algorithm is introduced into the image recovery in fractional Fourier domain after adaptation. When this algorithm is applied directly, its performance is good for smoothed image, but bad for unsmoothed image. Based on the diversity of fractional Fourier transform on its orders, this paper suggests a novel iterative algorithm, which extracts the information of the original image from amplitudes of its fractional Fourier transform at two orders. This new algorithm consists of two independent Gerchberg-Saxton procedures and an averaging operation in each circle. Numerical simulations are carried out to show its validity for both smoothed and unsmoothed images with most pairs of orders in the interval [0, 1].
Starting with the maximum-likelihood (ML) formulation, three iterative algorithms for approximate ML frequency estimation of a two-dimensional (2-D) complex sinusoid in white Gaussian noise are developed. Mean and var...
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Starting with the maximum-likelihood (ML) formulation, three iterative algorithms for approximate ML frequency estimation of a two-dimensional (2-D) complex sinusoid in white Gaussian noise are developed. Mean and variance analyses of the proposed methods are provided, which show that they are approximately unbiased and their performance achieves Cramer-Rao lower bound (CRLB) at sufficiently high signal-to-noise ratio (SNR) conditions. Computer simulation results are included to corroborate the theoretical development as well as to contrast the performance of the proposed algorithms with Kay's estimators and the CRLB.
A method to design an input phase mask for double-random phase-encoding optical encryption is proposed. The input phase mask is iteratively designed so that the extent of the Fourier spectrum of the product of an inpu...
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A method to design an input phase mask for double-random phase-encoding optical encryption is proposed. The input phase mask is iteratively designed so that the extent of the Fourier spectrum of the product of an input image and the input phase mask correspond to the space bandwidth of the optical system. By using the designed input phase mask, we show that the bit-error rate is improved. We also discuss the number of phase levels of the designed input phase mask. (c) 2006 Society of Photo-Optical Instrumentation Engineers.
This paper presents a linear constrained minimum variance multiuser detection (MUD) scheme for DS-CDMA systems, which makes full use of the available spreading sequences of the users as well as the relevant channel in...
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This paper presents a linear constrained minimum variance multiuser detection (MUD) scheme for DS-CDMA systems, which makes full use of the available spreading sequences of the users as well as the relevant channel information of the incoming rays in the construction of the constraint matrix. To further enhance the performance, a statistical optimum filter bank in combination with the developed minimum variance MUD with the partitioned linear interference canceller (PLIC) as the underlying structure is also addressed. The determination of the filter bank coefficients, however, calls for computationally demanding nonlinear programming. To alleviate the computational overhead, an iterative procedure is also proposed, which solves the Rayleigh quotient in each iteration. Furthermore, the expressions of the output signal to interference plus noise ratio (SINR) are also determined to provide further insights into the proposed approach. Conducted simulations validate the new scheme.
An algorithmic characterization of H-matrices was provided by Huang et al. [Comput. Math. Appl. 48 (2004) 1587-1601]. In this paper, we propose a new non-parameter method, which is always convergent in finite iterativ...
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An algorithmic characterization of H-matrices was provided by Huang et al. [Comput. Math. Appl. 48 (2004) 1587-1601]. In this paper, we propose a new non-parameter method, which is always convergent in finite iterative steps for H-matrices and needs fewer number of iterations than that of Huang et al.;we also provide an improved algorithm for a general matrix, which decreases the wasteful computations when the given matrix is not an H-matrix. Several numerical examples for the effectiveness of the proposed algorithms are presented. (c) 2006 Elsevier Inc. All rights reserved.
In this paper, we construct a reproducing kernel in spline subspaces and use the reproducing kernel to obtain a reconstruction formula from the weighted samples and incremental integral samples. We also improve the A-...
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In this paper, we construct a reproducing kernel in spline subspaces and use the reproducing kernel to obtain a reconstruction formula from the weighted samples and incremental integral samples. We also improve the A-P iterative algorithm, and use the algorithm to implement the reconstruction from weighted samples, and obtain the explicit convergence rate of the algorithm in spline subspaces. (C) 2005 Elsevier B.V. All rights reserved.
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