Evolutionary dynamics in a Lotka–Volterra competition model with impulsive periodic disturbance

In this paper, we develop a theoretical framework to investigate the influence of impulsive periodic disturbance on the evolutionary dynamics of a continuous trait, such as body size, in a general Lotka–Volterra‐type competition model. The model is formulated as a system of impulsive differential equations. First, we derive analytically the fitness function of a mutant invading the resident populations when rare in both monomorphic and dimorphic populations. Second, we apply the fitness function to a specific system of asymmetric competition under size‐selective harvesting and investigate the conditions for evolutionarily stable strategy and evolutionary branching by means of critical function analysis. Finally, we perform long‐term simulation of evolutionary dynamics to demonstrate the emergence of high‐level polymorphism. Our analytical results show that large harvesting effort or small impulsive harvesting period inhibits branching, while large impulsive harvesting period promotes branching. Copyright © 2015 John Wiley & Sons, Ltd.     

Convergence of goal‐oriented adaptive finite element methods for nonsymmetric problems

In this article, we develop convergence theory for a class of goal‐oriented adaptive finite element algorithms for second‐order nonsymmetric linear elliptic equations. In particular, we establish contraction results for a method of this type for Dirichlet problems involving the elliptic operator with A Lipschitz, symmetric positive definite, with b divergence‐free, and with . We first describe the problem class and review some standard facts concerning conforming finite element discretization and error‐estimate‐driven adaptive finite element methods (AFEM). We then describe a goal‐oriented variation of standard AFEM. Following the recent work of Mommer and Stevenson for symmetric problems, we establish contraction and convergence of the goal‐oriented method in the sense of the goal function. Our analysis approach is signficantly different from that of Mommer and Stevenson, combining the recent contraction frameworks developed by Cascon, Kreuzer, Nochetto, and Siebert; by Nochetto, Siebert, and Veeser; and by Holst, Tsogtgerel, and Zhu. We include numerical results, demonstrating performance of our method with standard goal‐oriented strategies on a convection problem. © 2015 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 32: 479–509, 2016     

A greedy meshless local Petrov–Galerkin methodbased on radial basis functions

The meshless local Petrov–Galerkin (MLPG) method with global radial basis functions (RBF) as trial approximation leads to a full final linear system and a large condition number. This makes MLPG less efficient when the number of data points is increased. We can overcome this drawback if we avoid using more points from the data site than absolutely necessary. In this article, we equip the MLPG method with the greedy sparse approximation technique of (Schaback, Numercail Algorithms 67 (2014), 531–547) and use it for numerical solution of partial differential equations. This scheme uses as few neighbor nodal values as possible and allows to control the consistency error by explicit calculation. Whatever the given RBF is, the final system is sparse and the algorithm is well‐conditioned. © 2015 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 32: 847–861, 2016     

基于GSPN的飞机测试性指标确定方法研究

针对现有的图像分割中自适应分割方法的研究难点,以及传统的模糊阈值分割法中存在窗宽不能自动获取的问题,在确定隶属函数的前提下,以图像的直方图为依据,利用分段计算和反变换的方法,提出了一种自适应模糊阈值的图像分割方法,并将该方法应用于机场目标的分割。该方法实现其窗口宽度的自适应选取,并且有效改善了模糊阈值法对直方图呈不明显双峰的图像分割困难的缺点,拓展了模糊阈值图像分割方法的适用范围,改善了模糊阈值分割方法的分割效果。实验结果表明,该方法对直方图呈单峰和多峰分布的的图像有较好的分割效果和效率。     

Energy-efficient Hardware Accelerators for the SA-DCT and Its Inverse

The explosive growth of the mobile multimedia industry has accentuated the need for efficient VLSI implementations of the associated computationally demanding signal processing algorithms. In particular, the short battery life caused by excessive power consumption of mobile devices has become the biggest obstacle facing truly mobile multimedia. We propose novel hardware accelerator architectures for two of the most computationally demanding algorithms of the MPEG-4 video compression standard––the forward and inverse shape adaptive discrete cosine transforms (SA-DCT/IDCT). These accelerators have been designed using general low-energy design philosophies at the algorithmic/architectural abstraction levels. The themes of these philosophies are avoiding waste and trading area/performance for power and energy gains. Each core has been synthesised targeting TSMC 0.09 μm TCBN90LP technology, and the experimental results presented in this paper show that the proposed cores improve upon the prior art.

Adaptive Beamforming and DOA Estimation Using Uniform Concentric Spherical Arrays with Frequency Invariant Characteristics

This paper proposes a new digital beamformer for uniform concentric spherical array (UCSA) having nearly frequency invariant (FI) characteristics. The basic principle is to transform the received signals to the phase mode and remove the frequency dependency of the individual phase mode through the use of a digital beamforming network. It is shown that the far field pattern of the array is determined by a set of weights and it is approximately invariant over a wide range of frequencies. FI UCSAs are electronic steerable in both the azimuth and elevation angles, unlike their concentric circular array counterpart. The frequency invariant characteristic of the FI UCSA also makes it possible to design separately the compensation network and beamformer weighting coefficients. The design of the compensation network is formulated as a second order cone programming (SOCP) problem and is solved optimally for minimax criterion. Thanks to the frequency invariant characteristic, traditional narrow band adaptive beamforming algorithms such as minimum variance beamforming (MVB) can be applied to the FI UCSA. Also, traditional narrow band 2-D direction of arrival (DOA) estimation algorithms such as unitary ESPRIT can be extended to broadband DOA estimation using FI UCSA. Simulation results show that the proposed adaptive beamformer using FI UCSA can obtain a higher output signal to inference plus noise ratio over the conventional tapped-delay line approach. Simulation results also show that FI UCSA has uniform beampattern and resolution around 360° in both azimuth and elevation angles, unlike FI uniform concentric circular array. The usefulness of the proposed UCSA-FIB in broadband 2-D DOA estimation is also verified by computer simulation.

Channel and Data Estimation for Ad Hoc Networks and Cognitive Radio

Estimation of channel and data characteristics by the receiver is important in adaptive wireless transmission protocols and in cognitive radio. This paper formulates the estimation problem with the help of an illustrative example from the IEEE 802.11a OFDM standard. The problem reduces to the estimation of the common component variance and mixing probabilities in a finite Gaussian mixture, with known values for component means. Using the known component means, μ₁, ... , μ _M , a set of non-linear transformations, and of the data (mixture random variable X) are used to develop convergent and computationally efficient estimators for both the noise variance and the vector of symbol probabilities. The estimation equations can be implemented recursively or with a batch processing algorithm. Asymptotic variances of the estimates and the Cramer–Rao minimum variance bounds are derived. The estimates converge to true unknowns even when the sequences of noise and data symbols are dependent sequences. The OFDM example is simulated with parameters corresponding to the highest acceptable error rate. For a time-varying channel model chosen from the literature, it is shown that our estimator receives considerably more than adequate amount of data during an average time interval of unchanging channel characteristics. Analytical results, numerical results and related issues are discussed.     

Adaptive frame methods for elliptic operator equations: the steepest descent approach

Massimo Fornasier^¶ Dipartimento di Metodi e Modelli Matematici per le Scienze Applicate, Università "La Sapienza" in Roma, Via Antonio Scarpa, 16/B, I-00161 Roma, Italy Rob Stevenson^|| Department of Mathematics, Utrecht University, PO Box 80.010, NL-3508 TA Utrecht, The Netherlands ^{This paper is concerned with the development of adaptive numericalmethods for elliptic operator equations. We are particularlyinterested in discretization schemes based on wavelet frames.We show that by using three basic subroutines an implementable,convergent scheme can be derived, which, moreover, has optimalcomputational complexity. The scheme is based on adaptive steepestdescent iterations. We illustrate our findings by numericalresults for the computation of solutions of the Poisson equationwith limited Sobolev smoothness on intervals in 1D and L-shapeddomains in 2D.}     

Adaptive Algorithms of Nonlinear Approximation with Finite Terms

This paper deals with realizable adaptive algorithms of the nonlinear approximation with finite terms based on wavelets. We present a concrete algorithm by which we may find the required index set Am for the greedy algorithm Gm^P（., Ψ）. This makes the greedy algorithm realize the near best approximation in practice. Moreover, we study the efficiency of the finite-term approximation of another Mgorithm introduced by Birge and Massart.     

测量噪声对波前重构精度的影响

 Hartmann-Shack波前传感器斜率测量误差是自适应光学系统中影响波前重构精度的一个主要误差来源。针对模式法波前重构算法,推导出了普遍适用的模式法波前重构误差传递系数计算公式;利用61单元自适应光学系统中的Hartmann-Shack波前传感器测量的斜率数据,验证了模式法波前重构误差传递系数计算公式的正确性。