Synchronization of Markovian jumping complex networks with event-triggered control

This paper investigates event-triggered synchronization for complex networks with Markovian jumping parameters.Nonlinear dynamics with Markovian jumping parameters is considered for each node in a complex network. By utilizing the proposed event-triggered strategy, and based on the Lyapunov functional method and linear matrix inequality technology,some sufficient conditions for synchronization of complex networks are derived whether the transition rate matrix for the Markov process is completely known or not. Finally, a numerical example is presented to illustrate the effectiveness of the proposed theoretical results.

Modified filter for mean elements estimation with state jumping

To investigate the real-time mean orbital elements(MOEs)estimation problem under the influence of state jumping caused by non-fatal spacecraft collision or protective orbit trans-fer,a modified augmented square-root unscented Kalman filter(MASUKF)is proposed.The MASUKF is composed of sigma points calculation,time update,modified state jumping detec-tion,and measurement update.Compared with the filters used in the existing literature on MOEs estimation,it has three main characteristics.Firstly,the state vector is augmented from six to nine by the added thrust acceleration terms,which makes the fil-ter additionally give the state-jumping-thrust-acceleration esti-mation.Secondly,the normalized innovation is used for state jumping detection to set detection threshold concisely and make the filter detect various state jumping with low latency.Thirdly,when sate jumping is detected,the covariance matrix inflation will be done,and then an extra time update process will be con-ducted at this time instance before measurement update.In this way,the relatively large estimation error at the detection moment can significantly decrease.Finally,typical simulations are per-formed to illustrated the effectiveness of the method.

My Jump 2应用程序测量大学生下肢垂直刚度的信度和效度

背景:证实My Jump 2应用程序测量下肢垂直刚度的信效度水平,可为其作为Kistler三维测力台测量下肢垂直刚度的替代方法提供可能性。目的:验证My Jump 2应用程序测量大学生下肢垂直刚度的信效度。方法:通过Kistler三维测力台和My Jump 2应用程序采集受试者的跳深数据并计算受试者的下肢垂直刚度。采用组内相关系数分析My Jump 2应用程序与Kistler三维测力台测得的数据,以验证My Jump 2应用程序的信度。将2个设备之间的偏倚值和平均值绘制成Bland-Altman图,验证2种测试方法之间的一致性。最后,使用克朗巴哈系数(α)和变异系数分析My Jump 2应用程序在30,40 cm高度的重测信度,使用皮尔逊积矩相关系数分析My Jump 2应用程序的相关性。结果与结论:①My Jump 2应用程序在测量下肢垂直刚度时具有较高的信效度;②同时由于其具有低成本、携带便捷和可用于大样本的场地测试的优势,可作为测力台的替代工具在大学生以及类似人群中对下肢垂直刚度进行测试。

A Brief Analysis of the Implication in “The Celebrated Jumping Frog of Calaveras County”

The Celebrated Jumping Frog of Calaveras County is a novel first published in 1865.It tells us a story taking place in the ancient mining camp of Angel's.By using analysis,the implication hidden behind the novel is explored here.That is,the abnormal social phenomena exist in the reality,the intrigue among people to gain profits and also the immoral measures people took for panning gold at the Gold Rush Era.

基于改进Event模型的通用航空器碰撞风险分析

随着通用航空的发展,空中交通流量将持续扩大,航空器碰撞风险增加。对Event模型进行改进,将拼接四棱锥碰撞盒代替原长方体碰撞盒,曲面间隔层代替平面间隔层,建立通用航空器碰撞风险模型。最后将塞斯纳172及运5B通用航空器作为实例对所建模型进行验证,结果表明,在两组均采用广义帕累托分布的条件下,改进后Event模型碰撞风险值分别为改进前的31.65%、14.98%,碰撞风险值较改进前大大减少,结果精度更高,能更好地评估交叉航路碰撞风险。

Biological Jumping Mechanism Analysis and Modeling for Frog Robot

This paper presents a mechanical model of jumping robot based on the biological mechanism analysis of frog. By biological observation and kinematic analysis the frog jump is divided into take-offphase, aerial phase and landing phase. We find the similar trajectories of hindlimb joints during jump, the important effect of foot during take-off and the role of forelimb in supporting the body. Based on the observation, the frog jump is simplified and a mechanical model is put forward. The robot leg is represented by a 4-bar spring/linkage mechanism model, which has three Degrees of Freedom （DOF） at hip joint and one DOF （passive） at tarsometatarsal joint on the foot. The shoulder and elbow joints each has one DOF for the balancing function of arm. The ground reaction force of the model is analyzed and compared with that of frog during take-off. The results show that the model has the same advantages of low likelihood of premature lift-off and high efficiency as the frog. Analysis results and the model can be employed to develop and control a robot capable of mimicking the jumping behavior of frog.

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed timevarying delays and Markovian jumping parameters.The addressed neural networks have a finite number of modes,and the modes may jump from one to another according to a Markov process.By construction of a suitable Lyapunov-Krasovskii functional,a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square.The criterion is formulated in terms of a set of linear matrix inequalities（LMIs）,which can be checked efficiently by use of some standard numerical packages.

Robust reliable H-infinity control for nonlinear uncertain stochastic time-delay systems with Markovian jumping parameters

This paper deals with the problems of robust reliable exponential stabilization and robust stochastic stabilization with H-infinity performance for a class of nonlinear uncertain time-delay stochastic systems with Markovian jumping parameters. The time delays are assumed to be dependent on the system modes. Delay-dependent conditions for the solvability of these problems are obtained via parameter-dependent Lyapunov functionals. Furthermore, it is shown that the desired state feedback controller can be designed by solving a set of linear matrix inequalities. Finally, the simulation is provided to demonstrate the effectiveness of the proposed methods.

Experimental investigation on single person's jumping load model

This paper presents a modified half-sine-squared load model of the jumping impulses for a single person. The model is based on a database of 22,921 experimentally measured single jumping load cycles from 100 test subjects. Threedimensional motion capture technology in conjunction with force plates was employed in the experiment to record jumping loads. The variation range and probability distribution of the controlling parameters for the load model such as the impact factor, jumping frequency and contact ratio, are discussed using the experimental data. Correlation relationships between the three parameters are investigated. The contact ratio and jumping frequency are identified as independent model parameters, and an empirical frequency-dependent function is derived for the impact factor. The feasibility of the proposed load model is established by comparing the simulated load curves with measured ones, and by comparing the acceleration responses of a single-degree-of-freedom system to the simulated and measured jumping loads. The results show that a realistic individual jumping load can be generated by the proposed method. This can then be used to assess the dynamic response of assembly structures.

OPTIMIZATION OF THE TAKE-OFF MOVEMENT OF SKI JUMPING WITH THE METHOD OF MATHEMATICAL PROGRAMMING

This paper is based on the finite and dispersed data which were obtained from the experiments of the wind tunnel and of the force measurement and from the high-speed photography. It analyses and optimizes the take-off movement of ski jumping with the theory of dynamics of systems of rigid bodies and with the method of mathematical programming. The paper describes the optimal take-off movement of ski jumping. Furthermore, it presents an example and compares the result with those of other papers published at home and abroad. The comparison shows that our computation and optimization are reasonable and well-grounded.

STOCHASTIC STABILITY OF UNCERTAIN RECURRENT NEURAL NETWORKS WITH MARKOVIAN JUMPING PARAMETERS

In this paper, global robust stability of uncertain stochastic recurrent neural networks with Markovian jumping parameters is considered. A novel Linear matrix inequal- ity（LMI） based stability criterion is obtained to guarantee the asymptotic stability of uncertain stochastic recurrent neural networks with Markovian jumping parameters. The results are derived by using the Lyapunov functional technique, Lipchitz condition and S-procuture. Finally, numerical examples are given to demonstrate the correctness of the theoretical results. Our results are also compared with results discussed in [31] and [34] to show the effectiveness and conservativeness.

Stability of stochastic neural networks with Markovian jumping parameters

The global asymptotical stability for a class of stochastic delayed neural networks （SDNNs） with Maxkovian jumping parameters is considered. By applying Lyapunov functional method and Ito＇s differential rule, new delay-dependent stability conditions are derived. All results are expressed in terms of linear matrix inequality （LMI）, and a numerical example is presented to illustrate the correctness and less conservativeness 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.

A comparative study of the self-propelled jumping capabilities of coalesced droplets on RTV surfaces and superhydrophobic surfaces

Understanding the mechanism of coalescence-induced self-propelled jumping behavior provides distinct insights in designing and optimizing functional coatings with self-cleaning and anti-icing properties.However,to date self-propelled jumping phenomenon has only been observed and studied on superhydrophobic surfaces,other than those hydrophobic surfaces with weaker but fairish water-repellency,for instance,vulcanized silicon rubber(RTV) coatings.In this work,from the perspective of thermodynamic-based energy balance aspect,the reason that self-propelled jumping phenomenon does not happen on RTV coatings is studied.The apparent contact angles of droplets on RTV coatings can be less than the theoretical critical values therefore cannot promise energy surplus for the coalesced droplets onside.Besides,on RTV and superhydrophobic surfaces,the droplet-size dependent variation characteristics of the energy leftover from the coalescence process are opposite.For the droplets coalescing on RTV coatings,the magnitudes of energy dissipations are more sensitive to the increase in droplet size,compared to that of released surface energy.While for superhydrophobic coatings,the energy generated during the coalescence process can be more sensitive than the dissipations to the change in droplet size.

Glucose Oxidase/Polypyrrole Biosensor Fabricated by Galvanostatic Electropolymerization Accompanied with a Potential Jumping

A galvanostatic glucose oxidase (GOD_x)/polypyrrole (Ppy) biosensor fabricated through a potential jumping process was reported.In spite of the instantaneous voltage jumping from 0.95 V to 1.7 V versus Ag/AgCl in the galvanostatic polymerization of pyrrole with commercial GOD_x,this GOD_x enzyme still could be successfully bundled with polypyrrole (Ppy).And,the results also confirmed that this glucose sensor not only possessed of better sensitivity to glucose than that fabricated from potentiometry or mild voltage elevating galvanometry for the similar preparing conditions but also exhibited two-week long-term stability.Finally,the kinetic data of Michalis constant (K_m) and Maximum current (I_m) for the optimized sensor were derived.The discovery this electro-modification process may disclose a novel method for fabricating the other enzyme biosensors.

Test and Analysis of the Sound Insulation Performance of Four Types of Timber Structure Floors under Jumping Excitation

To improve the impact sound insulation performance of building floors and meet the objective requirements for living comfort of residents,in this article,three kinds of elastic cushion materials,Portuguese cork board,BGL insulation sound insulation foam board,and EPP polypropylene plastic foam board,are applied to the sound insulation of a light frame wood floor structure of the same bedroom and compared to the ordinary floor.This study uses the transfer function method and transient excitation method to measure the sound insulation,damping ratio,and elastic modulus of materials,as well as the sound insulation of the floor under the jumping excitation method of daily behavior.Through comparative analysis,the results and factors of improving the sound insulation performance of the floor are obtained,according to which three types of elastic cushion materials and the floor covering composed of them have higher vibration and noise reduction performance.Among them,the overall sound insulation performance of BGL board floor is the highest,followed by EPP board and cork board floor,and ordinary OSB floor is the lowest.Under the jumping excitation method,three floating floors can improve the impact sound insulation performance of the middle and low-frequency bands.

Study on An Absolute Non-Collision Hash and Jumping Table IP Classification Algorithms

In order to classify packet, we propose a novel IP classification based the non-collision hash and jumping table trie-tree (NHJTTT) algorithm, which is based on noncollision hash Trie-tree and Lakshman and Stiliadis proposing a 2-dimensional classification algorithm (LS algorithm). The core of algorithm consists of two parts: structure the non-collision hash function, which is constructed mainly based on destination/source port and protocol type field so that the hash function can avoid space explosion problem; introduce jumping table Trie-tree based LS algorithm in order to reduce time complexity. The test results show that the classification rate of NHJTTT algorithm is up to 1 million packets per second and the maximum memory consumed is 9 MB for 10 000 rules. Key words IP classification - lookup algorithm - trie-tree - non-collision hash - jumping table CLC number TN 393.06 Foundation item: Supported by the Chongqing of Posts and Telecommunications Younger Teacher Fundation (A2003-03).Biography: SHANG Feng-jun (1972-), male, Ph.D. candidate, lecture, research direction: the smart instrument and network.

Improved delay-dependent globally asymptotic stability of delayed uncertain recurrent neural networks with Markovian jumping parameters

In this paper, we have improved delay-dependent stability criteria for recurrent neural networks with a delay varying over a range and Markovian jumping parameters. The criteria improve over some previous ones in that they have fewer matrix variables yet less conservatism. In addition, a numerical example is provided to illustrate the applicability of the result using the linear matrix inequality toolbox in MATLAB.

Robust stability analysis for Markovian jumping stochastic neural networks with mode-dependent time-varying interval delay and multiplicative noise

This paper is concerned with the problem of robust stability for a class of Markovian jumping stochastic neural networks （MJSNNs） subject to mode-dependent time-varying interval delay and state-multiplicative noise. Based on the Lyapunov-Krasovskii functional and a stochastic analysis approach, some new delay-dependent sufficient conditions are obtained in the linear matrix inequality （LMI） format such that delayed MJSNNs are globally asymptotically stable in the mean-square sense for all admissible uncertainties. An important feature of the results is that the stability criteria are dependent on not only the lower bound and upper bound of delay for all modes but also the covariance matrix consisting of the correlation coefficient. Numerical examples are given to illustrate the effectiveness.