Short correctness proofs for two self-stabilizing algorithms under the distributed daemon model

The distributed daemon model introduced by Burns in 1987 is a natural generalization of the central daemon model introduced by Dijkstra in 1974. In this paper, we show that a well-known shortest path algorithm is self-stabilizing under the distributed daemon model. Although this result has been proven only recently, the correctness proof provided here is from a different point of view and is much more concise. We also show that Bruell et al.’s center-finding algorithm is actually self-stabilizing under the distributed daemon model. Finally, we compute the worst-case stabilization times of the two algorithms under the distributed daemon model.     

Block monotone iterative algorithms for variational inequalities with nonlinear operators

Some block iterative methods for solving variational inequalities with nonlinear operators are proposed. Monotone convergence of the algorithms is obtained. Some comparison theorems are also established. Compared with the research work in given by Pao in 1995 for nonlinear equations and research work in given by Zeng and Zhou in 2002 for elliptic variational inequalities, the algorithms proposed in this paper are independent of the boundedness of the derivatives of the nonlinear operator.     

Genetic algorithms and cellular automata in aquifer management

A groundwater management problem is presented involving pumping cost minimization with both well discharges and well locations as decision variables. A grid of candidate well locations is set up and optimal arrangements of wells are sought within this discrete space. A genetic algorithm approach is presented with the following particular features: (a) A suitable scaling is applied to the objective function in order to alleviate its regionally flat behavior. (b) No penalty functions are involved in constraint handling. Instead, the feasible region is transformed into a rectangular domain. The transformation introduced is proved to be bijective. (c) A binary representation of well configurations is presented and compared to a combinatorial one. The binary representation necessitates the introduction of specially designed genetic operators. Besides purely genetic algorithms, the concept of cellular automaton is introduced as the basis of an alternative formulation of the optimization problem. The lattice of the cellular automaton provides the discrete set of candidate well positions. The well configuration is represented by a group of agents occupying an equal number of lattice sites. The agents change positions as dictated by the structure of the automaton and, also, by an associated genetic algorithm, which directs the evolution of the whole scheme toward an optimal configuration. An improved performance of this approach is noted and discussed in comparison to the purely genetic algorithm schemes of the present work. A simulated annealing approach is also applied to the same problem for comparison purposes. Finally, a new and more efficient hybrid annealing–genetic approach is introduced and discussed.     

GA-BP嵌套算法的理论及应用

分析了BP算法、遗传算法以及GA-BP-APARTING算法的特点,提出了GA-BP-NESTING算法.在人工神经网络的在线学习和离线学习方式下,分别对BP算法、GA算法、GA-BP-APARTING算法和GA-BP-NESTING算法进行了比较研究,研究发现:第一,网络初始权值的赋值对人工神经网络训练影响很大;第二,离线学习方式下GA-BP-NESTING算法效果最佳.     

Metrics of algebraic closures in pattern recognition problems with two nonoverlapping classes

It is shown that, in the pattern recognition problem with two nonoverlapping classes, the matrices of estimates of the object closeness are described by a metric. The transition to the algebraic closure of the model of recognizing operators of finite degree corresponds to the application of a special transformation of this metric. It is proved that the minimal degree correct algorithm can be found as a polynomial of a special form. A simple criterion for testing classification implementations is obtained.     

Performance of a recursive algorithm for polynomial predistorter design

In this article, based on least square estimation, a recursive algorithm for indirect learning structure predistorter is introduced. Simulation results show that of all polynomial predistorter nonlinear terms, higher-order （higher than 7th-order） nonlinear terms are so minor that they can be omitted in practical predistorter design. So, it is unnecessary to construct predistorter with higher-order polynomials, and the algorithm will always be stable. Further results show that even when 15th-order polynomial model is used, the algorithm is convergent after 10 iterations, and it can improve out-band spectrum of 20 MHz bandwidth signal by 64 dB, with a 1.2×10^11 matrix condition number.     

A two-dimensional matrix Padé-type approximation in the inner product space

By introducing a bivariate matrix-valued linear functional on the scalar polynomial space, a general two-dimensional (2-D) matrix Padé-type approximant (BMPTA) in the inner product space is defined in this paper. The coefficients of its denominator polynomials are determined by taking the direct inner product of matrices. The remainder formula is developed and an algorithm for the numerator polynomials is presented when the generating polynomials are given in advance. By means of the Hankel-like coefficient matrix, a determinantal expression of BMPTA is presented. Moreover, to avoid the computation of the determinants, two efficient recursive algorithms are proposed. At the end the method of BMPTA is applied to partial realization problems of 2-D linear systems.     

Adaptive random access algorithm with improved delay performance

We propose an adaptive random access algorithm for mobile environments with capture. The algorithm has a dynamic window size which is updated according to the traffic intensity. The packet arrival rate is tracked by employing sequential detection procedures. Simulations indicate that reducing the window size adaptively under heavy load conditions improves the average delay significantly. Copyright © 2001 John Wiley & Sons, Ltd.     

Numerical study on flanging and spring-back of stamped thick metal plate

A quasi-three-dimensional shell element model, which can be effectively used to simulate the flanging and spring-back deformation, is introduced into the independently developed CAE software, KMAS. In this model, a double surface contact algorithm, which allows the gap between punch and die to change, and a spring-back treatment scheme based on finite element meshing are described. And then the flanging and spring-back deformations of the retractor's kickstand of a railcar made of stamped thick metal plate are numerically simulated. The simulation results of flanging deformation are compared with those of international commercial software, PAM-STAMP, and experimental ones. Finally, a predicting scheme of spring-back quantily for this problem is given. Project supported by the National Natural Science Foundation of China (No. 19832020) and the Ministry of Education of China.