Matching inductive search bias and problem structure in continuous Estimation-of-Distribution Algorithms

Research into the dynamics of Genetic Algorithms (GAs) has led to the field of Estimation-of-Distribution Algorithms (EDAs). For discrete search spaces, EDAs have been developed that have obtained very promising results on a wide variety of problems. In this paper we investigate the conditions under which the adaptation of this technique to continuous search spaces fails to perform optimization efficiently. We show that without careful interpretation and adaptation of lessons learned from discrete EDAs, continuous EDAs will fail to perform efficient optimization on even some of the simplest problems. We reconsider the most important lessons to be learned in the design of EDAs and subsequently show how we can use this knowledge to extend continuous EDAs that were obtained by straightforward adaptation from the discrete domain so as to obtain an improvement in performance. Experimental results are presented to illustrate this improvement and to additionally confirm experimentally that a proper adaptation of discrete EDAs to the continuous case indeed requires careful consideration.     

Building nonredundant adaptive wavelets by update lifting

In this paper, we propose a technique for building adaptive wavelets by means of an extension of the lifting scheme. Our scheme comprises an adaptive update lifting step and a fixed prediction lifting step. The adaptivity consists hereof that the system can choose between two different update filters, and that this choice is triggered by the local gradient of the original signal. If the gradient is large (in some seminorm sense) it chooses one filter, if it is small the other. We derive necessary and sufficient conditions for the invertibility of such an adaptive system for various scenarios. Furthermore, we present some examples to illustrate our theoretical results.     

ADAPTIVE ALGORITHM FOR CONSISTENTMA PARAMETER ESTIMATION VIATHIRD ORDER CUMULANT

This paper addresses the problem of adaptive,consistent parameter estimation for a MA model from the 3rd order cumulant of the system output. The proposed adaptive algorithm is derived by using the new linear equation system (J. K. Tugnait, 1990), which is proved to have unique solution,and hence guarantees the consistence of the MA parameters. Simulation results are provided to show the performance of the new algorithm.     

一种改进的阵列天线方向图主波束快速赋形算法

改进的基于自适应天线阵理论的主波束赋形快速算法,可对任意阵列快速完成主波束赋形和旁瓣电平的控制.该算法通过局域权函数的迭代来减小综合方向图和期望方向图在主波束上的差别,旁瓣电平的控制可以通过在旁瓣峰值区域处加干扰来快速达到.该方法对主波束方向、宽度、形状和增益的控制非常成功.给出了一些算例说明这种算法的有效性.     

Adaptive finite element methods for high-speed compressible flows

We describe an adaptive finite element algorithm for solving the unsteady Euler equations. The finite element algorithm is based on a Taylor/Galerkin formulation and uses a very fast and efficient data structure to refine and unrefine the grid in order to optimize the approximation. We give a general version of the method which can be applied to moving grids with sliding interfaces and we present the results for a transient supersonic calculation of rotor-stator interaction.     

Efficient interval partitioning for constrained global optimization

A new efficient interval partitioning approach to solve constrained global optimization problems is proposed. This involves a new parallel subdivision direction selection method as well as an adaptive tree search. The latter explores nodes (intervals in variable domains) using a restricted hybrid depth-first and best-first branching strategy. This hybrid approach is also used for activating local search to identify feasible stationary points. The new tree search management technique results in improved performance across standard solution and computational indicators when compared to previously proposed techniques. On the other hand, the new parallel subdivision direction selection rule detects infeasible and suboptimal boxes earlier than existing rules, and this contributes to performance by enabling earlier reliable deletion of such subintervals from the search space.     

Application of possibility theory to investment decisions

Carlson and Fuller (2001, Fuzzy Sets and Systems, 122, 315–326) introduced the concept of possibilistic mean, variance and covariance of fuzzy numbers. In this paper, we extend some of these results to a nonlinear type of fuzzy numbers called adaptive fuzzy numbers (see Bodjanova (2005, Information Science, 172, 73–89) for detail). We then discuss the application of these results to decision making problems in which the parameters may involve uncertainty and vagueness. As an application, we develop expression for fuzzy net present value (FNPV) of future cash flows involving adaptive fuzzy numbers by using their possibilistic moments. An illustrative numerical example is given to illustrate the results.     

New high accuracy CMOS current conveyors

In this paper, a new CMOS CCII⁺ is proposed. The circuit is characterized by high precision in voltage tracking and exhibits very low input resistance. An adaptive voltage offset cancellation methodology is introduced and then applied to the proposed circuit. As a result, a higher accuracy CCII⁺ is presented. For both circuits, the voltage offset cancellation is independent of the input current and voltage. To demonstrate the strength of the proposed architectures, fair comparisons with Liu and Yodprasit CCII realizations are held.     

Point-diffraction interferometer for atmospheric adaptive optics in strong scintillation

This paper evaluates the performance of a point-diffraction interferometer for closed-loop adaptive optics. A point-diffraction interferometer was built using a modified Mach-Zehnder set-up. The system was used in closed-loop using a SLM to implement a square, 12 × 12, piston-only segmented corrector with a stroke of ±π. Its performance was tested for the case of atmospheric turbulence aberrations. The investigation showed, through simulation and experiment, that the point-diffraction interferometer worked in closed-loop operation in both uniform intensity and scintillated aberrations. Its robustness in the presence of phase discontinuities makes it a promising option for wavefront sensing in strong scintillation.     

频选MIMO信道下低复杂度PDA SIC算法

为了同时消除频率选择性MIMO系统中的天线间干扰（MAD和码间干扰（ISI），本文将基于信道矩阵QR分解的串行干扰消除（SIC）算法和概率数据辅助（PDA）均衡算法相结合，提出了一种低复杂度的软判决迭代均衡算法。该算法一方面很好地消除了MAI，另一方面将传统PDA算法中大量的矩阵运算简化为数值计算，降低了系统的计算复杂度，并获得了良好的性能。