Stability radius of implicit dynamic equations with constant coefficients on time scales

This paper deals with the stability radii of implicit dynamic equations on time scales when the structured perturbations act on both the coefficient of derivative and the right-hand side. Formulas of the stability radii are derived as a unification and generalization of some previous results. A special case where the real stability radius and the complex stability radius are equal is studied. Examples are derived to illustrate results.     

Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws

Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process.     

传感器输出特性的线性化回归程序设计

介绍了用面向对象程序设计方法编制的线性回归数据处理程序 ,该程序用于传感器实验数据的回归处理和特性曲线的绘制     

Evolving Teams of Predictors with Linear Genetic Programming

This paper applies the evolution of GP teams to different classification and regression problems and compares different methods for combining the outputs of the team programs. These include hybrid approaches where (1) a neural network is used to optimize the weights of programs in a team for a common decision and (2) a realnumbered vector (the representation of evolution strategies) of weights is evolved with each term in parallel. The cooperative team approach results in an improved training and generalization performance compared to the standard GP method. The higher computational overhead of team evolution is counteracted by using a fast variant of linear GP.     

Performance Analysis of Periodic Control for l1 and l∞ Disturbance Rejection

This paper presents a performance analysis of discrete time periodically time varying controllers for the rejection of l_p specific and uniform disturbances. Earlier results on l₂ performance are extended to l₁ and l_∞ performance to present a unified treatment of l_p performance for all p ε [1, ∞]. For a given linear time varying periodic controller, a linear time invariant controller is constructed and necessary and sufficient conditions are presented under which the linear time invariant controller gives strictly better l_p disturbance rejection performance than the time varying periodic controller.     

Solving multiple objective quasi-convex goal programming problems by linear programming

This study presents a novel means of resolving multiple objective goal programming (GP) problems with quasi-convex linear penalty functions. The proposed method initially expresses a quasi-convex function by the maximum operator of two convex functions, then solves it via a linear programming technique. The proposed method does not contain any zero–one variables; nor does it require dividing the multi-objective quasi-convex GP problem into large sub-problems as in conventional methods. Some illustrative examples are provided.     

基于矢量模型的语音线性预测研究

研究语音参数线性预测的并行处理问题。通过把语音源序列的相邻样本分组能够构成一个均方差平稳的语音向量自回归序列,在Hilbert空间中运用正交投影原理导出具有高度并行处理能力的一预测编码策略,由此可推出参数线性预测的并行处理自适应算法。同传统格型算法相比,这种算法的计算复杂度及存贮量有明显改善。最后通过仿真运算检测了算法的性能。     

Analyzing the structure of a class of linear automata over a ring $$ Z_{p^k } $$

Basic finite-automaton characteristics are established for the class of all linear automata and information-lossless automata over a ring. The complexities of solving problems of parametric identification and initial-state identification are analyzed. The sets of fixed points for mappings realized by initial automata are characterized. Canonical forms are proposed for linear automata over the ring. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 60–74, May–June 2008.     

Complexity and computability of solutions to linear programming systems

Through key examples and constructs, exact and approximate, complexity, computability, and solution of linear programming systems are reexamined in the light of Khachian's new notion of (approximate) solution. Algorithms, basic theorems, and alternate representations are reviewed. It is shown that the Klee-Minty example hasnever been exponential for (exact) adjacent extreme point algorithms and that the Balinski-Gomory (exact) algorithm continues to be polynomial in cases where (approximate) ellipsoidal centered-cutoff algorithms (Levin, Shor, Khachian, Gacs-Lovasz) are exponential. By model approximation, both the Klee-Minty and the new J. Clausen examples are shown to be trivial (explicitly solvable) interval programming problems. A new notion of computable (approximate) solution is proposed together with ana priori regularization for linear programming systems. New polyhedral constraint contraction algorithms are proposed for approximate solution and the relevance of interval programming for good starts or exact solution is brought forth. It is concluded from all this that the imposed problem ignorance of past complexity research is deleterious to research progress on computability or efficiency of computation.This research was partly supported by Project NR047-071, ONR Contract N00014-80-C-0242, and Project NR047-021, ONR Contract N00014-75-C-0569, with the Center for Cybernetic Studies, The University of Texas at Austin.     

露天磷矿数字配矿模型

露天磷矿选矿厂采用合理的配矿方案,对稳定入选磷矿的品位,增加选矿产率,降低生产成本有着重要的意义.为了提高入选磷矿石品位的均匀性和稳定性,提出了针对以入选磷矿品位为目标的从采矿场配矿到精矿仓配矿的整个生产环节的配矿方法.将采场内原矿、选矿厂原矿矿堆和选矿厂精矿仓均定义为矿堆,按照生产实际需求设定其属性.通过设定目标函数,实现使采矿场的开采原矿量最大,配矿方案总的运输距离最小,运输成本最低等目标.同时建立约束条件,使采矿场的开采原矿量要保证选矿厂正常生产,使每一矿堆的品位达到目标要求.最后,采集企业生产实际数据对模型加以验证,证明模型在指导露天磷矿山的生产过程中有重要的实际意义,配矿过程应成为矿山生产组织、管理的一个重要环节.