Reachable set estimation for discrete-time Markovian jump neural networks with unified uncertain transition probability

This paper focuses on the reachable set estimation for Markovian jump neural networks with time delay.By allowing uncertainty in the transition probabilities,a framework unifies and enhances the generality and realism of these systems.To fully exploit the unified uncertain transition probabilities,an equivalent transformation technique is introduced as an alternative to traditional estimation methods,effectively utilizing the information of transition probabilities.Furthermore,a vector Wirtinger-based summation inequality is proposed,which captures more system information compared to existing ones.Building upon these components,a novel condition that guarantees a reachable set estimation is presented for Markovian jump neural networks with unified uncertain transition probabilities.A numerical example is illustrated to demonstrate the superiority of the approaches.

An Improved Method for Estimating the Transition Probability Using Diameter Growth in Even-aged Forest Stands

The method of Zeng et al. (1991) employed diameter growth to estimate the transition probability of the matrix model in uneven-aged forest stands. In this paper the Weibull distribution for even-aged forest stands instead of uniform distribution chosen by Zeng is used. By comparing the results of the improved method with those of the original method of Zeng, it turns out that the improved method of Zeng given in this paper is more efficient.

Necessity of Exact Calculation for Transition Probability

This paper shows that exact calculation for transition probability can make some systems deviate fromFermi golden rule seriously. This paper also shows that the corresponding exact calculation of hopping rate inducedby phonons for deuteron in Pd-D system with the many-body electron screening, proposed by Ichimaru, can explainthe experimental fact observed in Pd-D system, and predicts that perfection and low-dimension of Pd lattice are veryimportant for the phonon-induced hopping rate enhancement in Pd-D system.

Brownian Motion of Decaying Particles: Transition Probability, Computer Simulation, and First-Passage Times

Recent developments in the measurement of radioactive gases in passive diffusion motivate the analysis of Brownian motion of decaying particles, a subject that has received little previous attention. This paper reports the derivation and solution of equations comparable to the Fokker-Planck and Langevin equations for one-dimensional diffusion and decay of unstable particles. In marked contrast to the case of stable particles, the two equations are not equivalent, but provide different information regarding the same stochastic process. The differences arise because Brownian motion with particle decay is not a continuous process. The discontinuity is readily apparent in the computer-simulated trajectories of the Langevin equation that incorporate both a Wiener process for displacement fluctuations and a Bernoulli process for random decay. This paper also reports the derivation of the mean time of first passage of the decaying particle to absorbing boundaries. Here, too, particle decay can lead to an outcome markedly different from that for stable particles. In particular, the first-passage time of the decaying particle is always finite, whereas the time for a stable particle to reach a single absorbing boundary is theoretically infinite due to the heavy tail of the inverse Gaussian density. The methodology developed in this paper should prove useful in the investigation of radioactive gases, aerosols of radioactive atoms, dust particles to which adhere radioactive ions, as well as diffusing gases and liquids of unstable molecules.

Inverse Transformation of Elliptical Relative State Transition Matrix

A new set of relative orbit elements (ROEs) is used to derive a new elliptical formation flying model in previous work. In-plane and out-of-plane relative motions can be completely decoupled, which benefits elliptical formation design. In order to study the elliptical control strategy and perturbation effects, it is necessary to derive the inverse transformation of the relative state transition matrix based on relative orbit elements. Poisson bracket theory is used to obtain the linear transformations between the two representations: the relative orbit elements and the geocentric orbital frame. In this paper, the details of these transformations are presented.

On the Gauge Invariance of the Transition Probability of a Charged Particle in Electromagnetic Field

This paper suggests a principle to find a unitary operator U which transforms non-physical quantity,zero-potential Hamiltonian Ho, into true physical quantity UHoU+ for a charged particle in classical electromagneticfield, and puts forward a unified form of constructing gauge-independent transition probabilities in this case. Differentmethods correspond to different unitary operators which satisfy the above-mentioned principle.

On the Gauge Invariance of The Transition Probability of A Charged Particle in Electromagnetic Field

This paper suggests a principle to find a unitary operator U which transforms non-physical quantity, zero-potential Hamiltonian H0, into true physical quantity UH0U? for a charged particle in classical electromagnetic field, and puts forward a unified form of constructing gauge-independent transition probabilities in this case. Different methods correspond to different unitary operators which satisfy the above-mentioned principle.

Research on the Applications of Probability Model and Matrix Transformation in Data Analysis and Management under the Environment of Information Time

In this paper, we research the probability theory and matrix transformation based technique to manage the data for processing and analysis. Clustering analysis research has a long history, over the decades, the importance and the cross characteristics with other research direction to get the affirmation of the people. The probability theory and linear algebra act as the powerful tool for analyzing and mining data. The experimental result illustrates the effectiveness. In the near future, we plan to conduct more theoretical analysis on the topic.

Correlation of Claudins6 (CLDN6) gene expression in meningioma tissue with the expression of matrix metalloproteinases (MMPs)/tissue inhibitors of matrix metalloproteinase (TIMPs) and epithelial-mesenchymal transition (EMT) genes

Objective:To study the correlation of Claudins6 (CLDN6) gene expression in meningioma tissue with the expression of matrix metalloproteinases (MMPs)/tissue inhibitors of matrix metalloproteinase (TIMPs) and epithelial-mesenchymal transition (EMT) genes.Methods:Meningioma tissue samples that were surgically removed in Yibin First People's Hospital between April 2014 and May 2017 were selected, normal arachnoid tissue samples that were collected from decompressive craniectomy in Yibin First People's Hospital during the same period were selected, and the expression of CLDN6, MMPs/TIMPs and EMT genes in tissues were determined.Results: CLDN6 protein expression in meningioma tissue was significantly lower than that in normal arachnoid tissue;EMMPRIN, MMP2, MMP9, Vimentin and N-cadherin protein expression in meningioma tissue were significantly higher than those in normal arachnoid tissue while TIMP1, TIMP2, E-cadherin andα-catenin protein expression were significantly lower than those in normal arachnoid tissue;EMMPRIN, MMP2, MMP9, Vimentin and N-cadherin protein expression in meningioma tissue with higher CLDN6 expression were significantly lower than those in meningioma tissue with lower CLDN6 expression while TIMP1, TIMP2, E-cadherin andα-catenin protein expression were significantly higher than those in meningioma tissue with lower CLDN6 expression. Conclusion: Lowly expressed CLDN6 gene in meningioma tissue can increase the hydrolysis activity of MMPs, induce epithelial-mesenchymal transition and thus promote the invasive growth of meningioma.

Correlation of annexin A2 expression with epithelial-mesenchymal transition and extracellular matrix degradation in bile duct carcinoma

Objective: To investigate the correlation of annexin A2 expression with epithelial-mesenchymal transition (EMT) and extracellular matrix (ECM) degradation in bile duct carcinoma. Methods: A total of 60 patients with primary bile duct carcinoma who accepted bile duct carcinoma laparotomy in our hospital between April 2009 and May 2017 were selected. The bile duct carcinoma tissue and adjacent normal tissue were kept during operation and enrolled in bile duct cancer group (n=60) and normal control group (n=60). The protein expression of annexin A2, EMT marker molecules, MMPs subtypes and TIMPs subtypes in two groups of specimens were detected, and Pearson test was used to evaluate the correlation of annexin A2 expression with EMT and ECM degradation in bile duct carcinoma tissue. Results: Annexin A2 expression in bile duct cancer group was higher than that in normal control group;E-cadherin, β-catenin and syndecan-1 protein expression in bile duct cancer group were lower than those in control group whereas P-cadherin and Vimentin protein expression were higher than those in normal control group;MMP-2, MMP-7 and MMP-9 protein expression in bile duct cancer group were higher than those in normal control group whereas TIMP-1 and TIMP-2 protein expression were lower than those in normal control group. Pearson test showed that the annexin A2 expression in bile duct carcinoma was directly correlated with the protein expression of EMT marker molecules, MMPs subtypes and TIMPs subtypes. Conclusion: annexin A2 increases in bile duct carcinoma, and it can regulate EMT and ECM degradation process to affect the disease outcome.

一种基于模型概率单调性变化的自适应IMM-UKF改进算法

针对现有交互式多模型(IMM)算法模型间切换迟滞和转换速率慢的缺点,提出一种基于模型概率单调性变化的自适应交互式多模型无迹卡尔曼滤波改进算法(mIMM-UKF)。该算法利用后验信息模型概率的单调性,对马尔可夫转移概率矩阵及模型估计概率进行二次修正,加快了匹配模型的切换速度及转换速率。仿真结果表明,与现有算法相比,该算法通过快速切换匹配模型,有效提高了水下目标跟踪精度。

广义θ-图和广义梅花图φ的奇异性

利用奇异图的邻接矩阵行列式等于零的方法讨论广义θ-图和广义梅花图φ的奇异性,分别给出广义θ-图θ(a_(1),a_(2),…,a_(k))和广义梅花图φ(a_(1),a_(2),…,a_(k))是奇异图的充分必要条件,并计算这两类图中奇异图发生的概率值.

基于改进自适应IMM算法的高速列车组合定位

针对列车高精度定位问题,该文提出基于改进自适应交互多模型(IMM)的高速列车高精度组合定位方法。首先,根据列车定位需求和各传感器特点,设计了卫星接收器、轮轴测速传感器、测速雷达以及单轴陀螺仪4种传感器的组合定位方案。然后,针对IMM融合滤波算法因先验信息不准导致固定参数设置不当的问题,引入Sage-Husa自适应滤波和转移概率矩阵(TPM)自适应更新集成为自适应IMM算法。针对多模型切换的滞后问题,利用子模型似然函数值能快速反映模型变化趋势的特点,将似然函数值设为判定标志,并引入判定窗对TPM矩阵元素进行修正,有效提升了模型的切换速度。最后,基于改进自适应IMM算法对4种传感器定位信息进行融合滤波,实现高速列车的高精度组合定位。仿真结果表明:改进后的算法相比其他自适应IMM算法提升定位精度1.6%~14.7%,并且能通过提高模型间切换速度来有效降低位置误差峰值,同时具备较好的抗噪性能。

基于局部变分贝叶斯推断的分布式交互式多模型估计

针对目前部分多模型算法预先设定运动模型转移概率矩阵对状态估计精度的不利影响,本文提出了一种基于局部变分贝叶斯推断的分布式交互式多模型估计算法.不同于传统交互式多模型估计中运动模型转移概率矩阵为先验已知的假设条件,在分布融合估计框架下,首先基于最小化Kullback-Leibler散度准则的递归优化策略实现对运动模型转移概率矩阵的预测与更新;在此基础上,结合变分贝叶斯推断实现对当前时刻目标状态与模型概率的联合估计;最后依据协方差交叉融合策略完成对局部状态估计融合.仿真结果表明:新算法通过对运动模型转移概率矩阵以及模型概率自适应在线估计,有效提升了机动目标的状态估计精度.

基于分形理论的城市空间结构及其影响因素研究——以贵阳市为例

以贵阳市为研究区,以2010、2020年各土地利用类型数据为基础,采用分形理论探究贵阳市土地利用的变化速度和幅度,并分析贵阳市土地空间结构变化的驱动因素。结果表明:(1)贵阳市主要以耕地和林地为主,研究期间耕地、林地、草地等农业用地面积下降,建设用地和水体面积增加显著。(2)研究期间贵阳市各地类分形维数相差较大,整体边界维数呈上升趋势,形态维数下降,说明城市空间结构不规则性增加,城市土地利用复杂化,紧凑性降低。(3)贵阳市土地利用类型的变化是自然、人为因素共同导致的,尤其是经济与政策的影响。

基于矩阵乘积压缩态的动态可扩展秘密共享方案

目前,基于纠缠态的量子秘密共享(quantum secret sharing,QSS)方案未充分利用纠缠态的概率振幅潜力.然而,纠缠态的概率振幅是量子信息学的一个关键特性,在量子计算和量子通信等领域有着广泛的应用潜力.值得注意的是,纠缠态可以通过矩阵乘积态(matrix product state,MPS)有效表达.利用MPS对纠缠态进行表征,能够准确地揭示与概率振幅相关的纠缠特性.本研究证明利用MPS表征纠缠态,可以将一个W态压缩为一个单光子和一个矩阵,展示一种新的技术路径.此外,本研究还提出MPS与秘密共享方案之间的创新互操作性,即通过压缩允许量子份额与共享的量子态之间形成非一对一的映射关系.这种方法可能提供一种更高效的方式来实现量子信息的编码和传输,对于量子秘密共享尤为重要.同时,我们提出的QSS方案具有动态特性,能够根据需要轻松地添加或移除参与者,以更好地适应参与者需求的变化,并在实际应用场景中展现出更高的实用性和适应性.本文的方案能够在保持高效纠缠利用的同时,满足系统的多元需求,包括但不限于通信安全性、数据传输率和系统的可扩展性.

裙带菜多糖抑制肝癌细胞增殖和迁移的机制

目的探讨裙带菜多糖(sulfated polysaccharide from Undaria pinnatifida,SPUP)对肝癌细胞增殖、迁移的影响及潜在机制。方法MTT和克隆形成实验检测SPUP对肝癌细胞HepG2、SMMC-7721增殖的影响;Hoechst 33258染色和Western blot法检测SPUP干预后对HepG2、SMMC-7721细胞凋亡的影响;Transwell和划痕法检测HepG2、SMMC-7721细胞的迁移和侵袭;免疫荧光和Western blot法检测SPUP对肝癌细胞自噬、上皮-间质转化(epithelial-mesenchymal transition,EMT)和基质金属蛋白酶2(matrix metalloproteinase 2,MMP-2)、MMP-9蛋白的影响。结果SPUP对HepG2、SMMC-7721细胞有短期和长期的抑制增殖作用,对正常肝细胞L-02无明显抑制作用,SPUP可促进两种肝癌细胞凋亡和自噬水平。同时,SPUP可以抑制肝癌细胞的迁移侵袭能力,降低EMT和MMPs水平。结论SPUP通过促进凋亡和自噬、抑制EMT和MMPs,进而抑制肝癌细胞的增殖和迁移。

基于Relief算法的不平衡数据分类分级算法仿真

不平衡数据的分类分级是保证大数据技术高效使用过程中不可缺少的环节,但分类分级过程易受数据属性、冗余性、不均衡性等问题的干扰。为解决上述问题,提出不平衡数据朴素贝叶斯分类分级算法。采用合成少数类过采样技术降低数据的不平衡度,通过距离相关系数与最大信息系数完成不平衡数据的特征选择与筛选,采用Relief算法对筛选的特征做权重分配,并输入到朴素贝叶斯模型中实现分类,再结合动态阈值算法完成数据的分级。实验结果表明,所提算法的运行时间短、分类精度高,能够有效提升数据处理效果。

非齐次树上非齐次马氏链转移矩阵的一个极限性质

通过引入样本散度的概念和构造辅助非负鞅,利用Doob鞅收敛定理给出了非齐次树上k重非齐次马氏链转移矩阵的一个极限性质.

基于改进蚁群优化算法的AUV三维路径规划

针对蚁群算法在三维路径规划时收敛速度慢且难以收敛至最优的缺点,提出一种新的改进蚁群算法,并将其应用于自主式水下机器人(autonomous underwater vehicle,AUV)三维路径规划。与现有算法相比,改进算法优点主要体现在3个方面:首先,引进伪随机状态转移概率提升算法全局搜索能力;其次,将距离和轨迹限定因子引入启发式函数,距离因子保证搜索不断趋近目标点,在轨迹限定因子约束下,轨迹累计转角更小,以此提升收敛速度和精度;最后,通过扩大信息素增量差距并逐步提高信息素衰减系数,进一步提高路径规划效率。实验结果表明,改进蚁群算法能够获得累计转角更小路径,且路径长度更小,收敛速度更快。