A New Chaotic Parameters Disturbance Annealing Neural Network for Solving Global Optimization Problems

Since there were few chaotic neural networks applicable to the global optimization, in this paper, we propose a new neural network model ? chaotic parameters disturbance annealing (CPDA) network, which is superior to other existing neural networks, genetic algorithms, and simulated annealing algorithms in global optimization. In the present CPDA network, we add some chaotic parameters in the energy function, which make the Hopfield neural network escape from the attraction of a local minimal solution and with the parameter annealing, our model will converge to the global optimal solutions quickly and steadily. The converge ability and other characters are also analyzed in this paper. The benchmark examples show the present CPDA neural network's merits in nonlinear global optimization.

Adaptive Anti-Synchronization Between Different Chaotic/Hyperchaotic Systems with Fully Unknown Parameters

The anti-synchronization between different chaotic/hyperchaotic systems with fully unknown parameters is considered in detail. Based on Lyapunov stability theory, the adaptive control schemes and parameter update rules are designed in this paper. Two numerical examples show the effectiveness and feasibility of the proposed method.

Stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks with mixed delays and the Wiener process based on sampled-data control

We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality （LMI） approach. The Lyapunov–Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions （e.g., time derivative is smaller than one） are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.

参数化可配置IP核浮点运算器的设计与实现

将参数化可配置IP核的设计方法引入到浮点运算器设计中,通过设计时提取的可用参数,将浮点运算器设计成为参数化、可配置、可重用的IP核。通过仿真验证了实现参数化IP核浮点运算器的可行性和有效性。

Parameters identification of chaotic systems based on artificial bee colony algorithm combined with cuckoo search strategy

Artificial bee colony(ABC) algorithm is motivated by the intelligent behavior of honey bees when seeking a high quality food source. It has a relatively simple structure but good global optimization ability. In order to balance its global search and local search abilities further, some improvements for the standard ABC algorithm are made in this study. Firstly, the local search mechanism of cuckoo search optimization(CS) is introduced into the onlooker bee phase to enhance its dedicated search; secondly, the scout bee phase is also modified by the chaotic search mechanism. The improved ABC algorithm is used to identify the parameters of chaotic systems, the identified results from the present algorithm are compared with those from other algorithms. Numerical simulations, including Lorenz system and a hyper chaotic system, illustrate the present algorithm is a powerful tool for parameter estimation with high accuracy and low deviations. It is not sensitive to artificial measurement noise even using limited input data.

基于动态状态观测器的混沌系统同步设计的参数化方法

研究了在有界干扰情况下一类非线性反馈混沌系统的同步动态观测器设计问题。基于Sylvester矩阵方程的参数化解,给出了非线性反馈混沌系统的同步动态观测器矩阵的所有参数化表达式,其所含参量为混沌系统控制设计提供了全部自由度,可适当选择自由参量满足某些鲁棒性指标。最后,数值算例及其仿真结果表明本文所提非线性反馈混沌系统的同步动态观测器的参数化设计方法是简单有效的。

Chaotic characteristics and attractor evolution of friction noise during friction process

Friction experiments are conducted on a ring-on-disk tribometer, and friction noise produced during the friction process is extracted by a microphone. The phase trajectory and chaotic parameters of friction noise are obtained by phase-space reconstruction, and its attractor evolution is analyzed. The results indicate that the friction noise is chaotic because the largest Lyapunov exponent is positive. The phase trajectory of the friction noise follows a "convergence-stability-divergence" pattern during the friction process. The friction noise attractor begins forming in the running-in process, and the correlation dimension D increases gradually. In the stable process, the attractor remains steady, and D is stable. In the last step of the process, the attractor gradually disappears, and D decreases. The friction noise attractor is a chaotic attractor. Knowledge of the dynamic evolution of this attractor can help identify wear state changes from the running-in process to the steady and increasing friction processes.

基于全维PI观测器的混沌系统鲁棒故障检测设计

研究了在干扰存在情况下基于全维PI观测器的混沌系统鲁棒故障检测设计问题。基于一类Sylvester矩阵方程的参数化解,给出了干扰和残差信号解耦的充要条件,并建立了具有鲁棒故障检测功能的全维PI观测器设计的参数化方法。Lorenz混沌系统的数值算例及其计算结果表明：在干扰存在的情况下,基于全维PI观测器的混沌系统鲁棒故障检测设计方法简单有效。