基于固定增量单样本感知器的AdaBoost算法

针对传统AdaBoost算法在分类过程中时间复杂度和算法学习复杂度较高的问题,提出一种改进的算法AdaBoostFISP。以固定增量单样本感知器为弱分类器,在感知器的权值更新上采用固定增量代替变量增量,从而减少运算时间、降低学习复杂度。实验结果证明了该算法在预测准确性、学习复杂度和时间复杂度等方面的优势。     

基于定长时隙的多跳Ad Hoc网络DCF协议马尔可夫链模型

指出了现有的基于不定长时隙的DCF协议马尔可夫链模型的局限性,并在详细分析多跳ad hoc 网络环境中DCF 协议建模的难点问题基础上,提出了一种基于定长时隙的多跳ad hoc 网络DCF 协议马尔可夫链模型.通过模型的求解,得到了反映多跳ad hoc 网络饱和吞吐量性能的相关性能指标的理论值,并结合GloMoSim 网络仿真环境中的仿真实验,证明了模型的有效性.     

Coupled common fixed point theorems for a pair of commuting mappings in partially ordered complete metric spaces

The purpose of this paper is to establish a coupled coincidence point for a pair of commuting mappings in partially ordered complete metric spaces. We also present a result on the existence and uniqueness of coupled common fixed points. An example is given to support the usability of our results.     

Some fixed point theorems in 1-M-complete fuzzy metric-like spaces

Very recently, in order to unify the notions of fuzzy metric space and metric-like space, Shukla and Abbas introduced the concept of fuzzy metric-like space and proved some fixed-point results in this setting. In this article, we modify the notion of Cauchy sequence and completeness to generalize their results. Thus, we extend their theorems to a more general framework, which is also appropriate to generalize some recent, well-known results in this line of research. Furthermore, several examples are presented to illustrate the significance of our results.     

一种新的双足机器人模型设计与相关研究

针对双足机器人最简模型在行走过程中出现摆动腿足部擦地的问题,提出了一种通过摆动腿膝关节弯曲达到摆动腿缩短的新模型。当摆动腿开始摆动时,摆动腿膝关节弯曲锁定,摆动腿缩短;当摆动腿摆动到最大位置时,膝关节解锁,摆动腿伸直再锁定,此后摆动腿回摆,系统变为直腿模型。采用脚后跟冲击控制,在摆动腿落地前,拖后的支撑腿与地面接触处施加一指向髋关节的瞬时冲击力,冲击力可以减小摆动腿着地时能量的损耗,同时驱动被动机器人向前行走。设计了迭代学习控制算法,找到极限环与不动点,实现不同给定期望步长跟踪的冲击力的计算。仿真结果表明,迭代学习控制可以有效的实现不同期望步长的跟踪,可以很快的找到机器人系统的不动点,通过收敛的相平面,得到稳定的极限环,保证了机器人行走过程稳定。     

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.     

Approximate fixed point sequence for a finite family of asymptotically pseudocontractive mappings

Let E be a real Banach space and K be a nonempty, closed, convex, and bounded subset of E. Let T_i:K→K, i=1,2,…,N, be N uniformly L-Lipschitzian, uniformly asymptotically regular with sequences {ε_n}, and asymptotically pseudocontractive mappings with sequences , where {ε_n} and , i=1,2,…,N, satisfy certain mild conditions. Let a sequence {x_n} be generated from x₁K by

for all integers n1, where T_n=T_n(modN), {u_n} be a sequence in K, and {λ_n}, {θ_n} and {μ_n} are three real sequences in [0,1] satisfying appropriate conditions; then x_n−T_lx_n→0 as n→∞ for each l{1,2,…,N}.     

A high-order compact method for nonlinear Black–Scholes option pricing equations of American options

Due to transaction costs, illiquid markets, large investors or risks from an unprotected portfolio the assumptions in the classical Black–Scholes model become unrealistic and the model results in nonlinear, possibly degenerate, parabolic diffusion–convection equations. Since in general, a closed-form solution to the nonlinear Black–Scholes equation for American options does not exist (even in the linear case), these problems have to be solved numerically. We present from the literature different compact finite difference schemes to solve nonlinear Black–Scholes equations for American options with a nonlinear volatility function. As compact schemes cannot be directly applied to American type options, we use a fixed domain transformation proposed by ?ev?ovi? and show how the accuracy of the method can be increased to order four in space and time.