一般脉冲系统的Melnikov函数构造方法及其应用

利用摄动法给出了一般脉冲系统Melnikov函数构造方法,得到脉冲信号作用下一般非线性系统Melnikov方法.为考察方法的有效性,将方法应用到脉冲信号作用下Duffing系统的混沌预测中去,通过方法得到脉冲信号作用下Duffing系统出现混沌的阈值曲线,数值实验结果验证理论结果的正确性.     

分数阶Duffing混沌系统的动力性态及其由单一主动控制的混沌同步

随着物理与技术的深入研究,分数阶非线性系统的动力性态及其分数阶混沌系统的同步成为研究的焦点.研究了分数阶Duffing系统的动力性态包括混沌性质,并且由分数阶非线性稳定性准则得到了分数阶非自治系统的混沌同步.特别地,研究了由单一主动控制的分数阶Duffing系统的同步.相应的数值结果演示了方法的有效性.     

基于EMD方法的混沌信号中周期分量的提取

提出一种从Duffing振子产生的混沌信号中提取谐波分量的方法．依据任何信号由不同的固有简单振动模态组成的概念,利用经验模式分解（EMD）方法,将混沌信号分离为不同的内在模态函数(IMF),并在特定参数下从中分解出单一频率成分的谐波信号,从而成功地将混沌信号和谐波分量分离．仿真实验都表明该方法非常有效．     

基于Adomian分解法的分数阶Bao混沌系统动力学分析与电路实现

采用Adomian分解法从分数阶(0.9阶)Bao系统的混沌相图、分岔图、最大Lyapunov指数(MLE)以及SE与CO复杂度等数值仿真分析研究了该系统复杂的动力学特性.又基于整数阶混沌电路的设计方法,设计了硬件电路,实现了该分数B ao混沌系统,最后,观测示波器电路实验结果与理论分析结果相一致,从而进一步揭示了此类分数阶过渡混沌系统的可实现性与混沌特性.     

窄带随机噪声作用下非线性系统的响应

研究了Duffing振子在窄带随机噪声激励下的主共振响应和稳定性问题.用多尺度法分离了系统的快变项,讨论了系统的阻尼项、随机项等对系统响应的影响.在一定条件下,系统具有两个均方响应值.数值模拟表明方法是有效的.     

Duffing简谐振子同伦分析法求解

利用同伦分析方法求解了Duffing简谐振子,数值确定了变形方程中的辅助参数,得到了一族响应和频率的近似周期解,该解与精确解符合很好,结果表明,同伦分析法在求解强非线性振子时,仍然是一种行之有效的方法.     

谐和与随机噪声联合作用下Duffing振子的双峰稳态密度

研究Duffing振子在谐和与随机噪声联合作用下系统响应的双峰稳态概率密度问题．用多尺度法分离了系统的快变项,得到了系统慢变项满足的随机微分方程．用线性化方法求出了双峰稳态概率密度的表达式．数值模拟表明提出的方法是有效的．     

非线性Duffing扰动振子共振机制的研究

研究了一类广义Duffing扰动共振机制.利用泛函分析同伦映射方法,构造了求得问题渐近解的迭代关系式.首先求出了Duffing模型的初始近似函数;其次利用迭代关系依次求出了模型的各次渐近解;然后通过举例,说明了用泛函同伦映射方法得到的广义Duffing扰动振子随机共振机制的近似解简单而有效.讨论了得到的渐近解的意义.     

一类具有非光滑周期扰动Duffing系统的混沌预测

研究了一类具有非光滑周期扰动Duffing系统的动力学行为,尝试采用Fourier级数展开的方法来处理系统的非光滑特性,并在此基础上利用Melnikov方法给出了该系统出现混沌的解析条件.最后,数值模拟的结果显示了该方法的有效性.     

附加非线性振子的双稳态电磁式振动能量捕获器动力学特性研究

随着微机电科技的进步,利用环境振动进行系统自供电已经成为目前非线性动力学研究的热点.将质量-弹簧-阻尼系统与双稳态振动能量捕获系统相结合,提出了附加非线性振子的双稳态电磁式振动能量捕获器,建立系统的力学模型及控制方程.通过数值仿真研究了简谐激励下质量比和调频比发生变化时附加非线性振子的双稳态电磁式振动能量捕获器的动力学响应.通过与附加线性振子双稳态系统的对比,获得了上述参数对附加非线性振子的双稳态电磁式振动能量捕获器发生大幅运动的影响规律,显示出附加非线性振子的双稳态电磁式振动能量捕获器的优越性,并获得了附加非线性振子的双稳态电磁式振动能量捕获器发生连续大幅混沌运动的最优参数配合.上述研究结果为双稳态电磁式振动能量捕获系统的相关研究提供了理论基础.     

Bounds on the size of tetrahedralizations

This paper gives lower and upper bounds on the complexity of triangulating the region between polyhedra. Particular attention is given to the case of convex polyhedra and terrains. The first author was suported in part by NSF Grant CCR-90-02352 and The Geometry Center, University of Minnesota, an STC funded by NSF, DOE, and Minnesota Technology, Inc. The second author was supported in part by NSF Grant PHY-90-21984.     

Competitive on-line coverage of grid environments by a mobile robot

We describe in this paper two on-line algorithms for covering planar areas by a square-shaped tool attached to a mobile robot. Let D be the tool size. The algorithms, called Spanning Tree Covering (STC) algorithms, incrementally subdivide the planar area into a grid of D-size cells, while following a spanning tree of a grid graph whose nodes are 2D-size cells. The two STC algorithms cover general planar grids. The first, Spiral-STC, employs uniform weights on the grid-graph edges and generates spiral-like covering patterns. The second, Scan-STC, assigns lower weights to edges aligned with a particular direction and generates scan-like covering patterns along this direction. Both algorithms cover any planar grid using a path whose length is at most (n+m)D, where n is the total number of D-size cells and mn is the number of boundary cells, defined as cells that share at least one point with the grid boundary. We also demonstrate that any on-line coverage algorithm generates a covering path whose length is at least (2−)l_opt in worst case, where l_opt is the length of the optimal off-line covering path. Since (n+m)D2l_opt, the bound is tight and the STC algorithms are worst-case optimal. Moreover, in practical environments mn, and the STC algorithms generate close-to-optimal covering paths in such environments.     

Proper classes as members of extended sets

Conclusion It might be argued that STC is superfluous. In defense we reply that STC seems the most natural theory for handling theM andK . In NBG^AI the development is quite artificial. An even more fundamental reply is that those who wish to make puritannical restrictions on set theory forbidding inaccessible sets may have their holiday with inaccessible extended sets.Inconsistent multiplicities (which Cantor called absolutely infinites) are themselves relative to a system, or briefly, the absolute is relative.The author is deeply indebted to Professor A. Robinson for fruitful suggestions, general insights, and biting criticism.     

Every arrangement extends to a spread

Supported in part by NSA grant MDA904-89-H-2038, PSC-CUNY grant 662330, and the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), a National Science Foundation Science and Technology Center under NSF grant STC88-09648.     

Low-order self-tuner for fault-tolerant control of a class of unknown nonlinear stochastic sampled-data systems

Based on the modified state-space self-tuning control (STC) via the observer/Kalman filter identification (OKID) method, an effective low-order tuner for fault-tolerant control of a class of unknown nonlinear stochastic sampled-data systems is proposed in this paper. The OKID method is a time-domain technique that identifies a discrete input–output map by using known input–output sampled data in the general coordinate form, through an extension of the eigensystem realization algorithm (ERA). Then, the above identified model in a general coordinate form is transformed to an observer form to provide a computationally effective initialization for a low-order on-line “auto-regressive moving average process with exogenous (ARMAX) model”-based identification. Furthermore, the proposed approach uses a modified Kalman filter estimate algorithm and the current-output-based observer to repair the drawback of the system multiple failures. Thus, the fault-tolerant control (FTC) performance can be significantly improved. As a result, a low-order state-space self-tuning control (STC) is constructed. Finally, the method is applied for a three-tank system with various faults to demonstrate the effectiveness of the proposed methodology.     

Effort estimates through project complexity

This paper reports the results obtained from use of project complexity parameters in modeling effort estimates. It highlights the attention that complexity has recently received in the project management area. After considering that traditional knowledge has consistently proved to be prone to failure when put into practice on actual projects, the paper endorses the belief that there is a need for more open-minded and novel approaches to project management. With a view to providing some insight into the opportunities that integrate complexity concepts into model building offers, we extend the work previously undertaken on the complexity dimension in project management. We do so analyzing the results obtained with classical linear models and artificial neural networks when complexity is considered as another managerial parameter. For that purpose, we have used the International Software Benchmarking Standards Group data set. The results obtained proved the benefits of integrating the complexity of the projects at hand into the models. They also addressed the need of a complex system, such as artificial neural networks, to capture the fine nuances of the complex systems to be modeled, the projects.     

Fixed‐parameter decidability: Extending parameterized complexity analysis

We extend the reach of fixed‐parameter analysis by introducing classes of parameterized sets defined based on decidability instead of complexity. Known results in computability theory can be expressed in the language of fixed‐parameter analysis, making use of the landscape of these new classes. On the one hand this unifies results that would not otherwise show their kinship, while on the other it allows for further exchange of insights between complexity theory and computability theory. In the landscape of our fixed‐parameter decidability classes, we recover part of the classification of real numbers according to their computability. From this, using the structural properties of the landscape, we get a new proof of the existence of P ‐selective bi‐immune sets. Furthermore, we show that parameter values in parameterized sets in our uniformly fixed‐parameter decidability classes interact with both instance complexity and Kolmogorov complexity. By deriving a parameter based upper bound on instance complexity, we demonstrate how parameters convey a sense of randomness. Motivated by the instance complexity conjecture, we show that the upper bound on the instance complexity is infinitely often also an upper bound on the Kolmogorov complexity.     

基于模糊证据推理的汽车制造产业网络环境复杂性测度

环境复杂性是汽车制造产业网络复杂性的主要诱因。利用指标波动程度测度复杂性的思想,建立表征汽车制造产业网络外部环境的指标体系,构建指标变动程度的模糊信度结构模型,运用模糊证据推理算法结合熵值理论对多指标进行信息融合,并利用灰色关联分析方法评估复杂性测度结果。通过2002~2012年汽车行业数据的实证研究,结果表明:经济环境与国际环境的波动是导致汽车制造产业网络复杂性的最主要因素,技术环境和市场环境次之;近10年来我国汽车制造产业网络外部环境经历了两次较大波动,总体复杂性呈现增长趋势。本研究可为汽车产业环境复杂性测度及应对提供思路参考。     

List homomorphisms of graphs with bounded degrees

In a series of papers, we have classified the complexity of list homomorphism problems. Here, we investigate the effect of restricting the degrees of the input graphs. It turns out that the complexity does not change (except when the degree bound is two). We obtain similar results on restricting the size of the lists.We contrast these results with facts about variants of the list homomorphism problem, where restricting the degrees can have an important effect on the complexity.     

On the linear complexity of Hall’s sextic residue sequences over $${ GF}(q)$$

In this paper, we derive the linear complexity of Hall’s sextic residue sequences over the finite field of odd prime order. The order of the field is not equal to a period of the sequence. Our results show that Hall’s sextic residue sequences have high linear complexity over the finite field of odd order. Also we estimate the linear complexity of series of generalized sextic cyclotomic sequences. The linear complexity of these sequences is larger than half of the period.