Optimal linear estimation for continuous stochastic systems with random observation delays

This paper is concerned with the linear minimum mean square error estimation for Itô‐type differential equation systems with random delays, where the delay process is modeled as a finite‐state Markov chain. By first introducing a set of equivalent delay‐free observations and then defining two reorganized Markov chains, the estimation problem of random delayed systems is reduced to the one of delay‐free Markov jump linear systems. The estimator is derived by using the innovation analysis method based on the Itô differential formula. And the analytical solution to this estimator is given in terms of two Riccati differential equations that are of finite dimensions. Conditions for existence, uniqueness, and stability of the steady‐state optimal estimator are studied for time‐invariant cases. In this case, the obtained estimator is very easy to implement, and all calculation can be performed off line, leading to a linear time‐invariant estimator. Copyright © 2011 John Wiley & Sons, Ltd.     

参数稀疏信号非均匀采样性能分析

提出了一种参数稀疏信号的时间交替周期非均匀采样方案。相对于非均匀采样,周期非均匀采样可以在降低系统复杂度的前提下依然保持较高的转换速率。通过仿真证明,非均匀采样样本的超分辨率特性可以提高非线性最小二乘周期图谱估计的重构性能。     

丰田生产方式在企业中的运用

根据当代世界经济发展趋势,国内外先进企业为保持创新力经济能力纷纷采用丰田生产方式并取得了巨大成就,得出丰田生产方式在企业中运用的必要性。本文阐述了丰田生产方式TPS屋的构成,并分析了他在国内外企业发展过程中的作用。实践证明,企业践行丰田生产方式可有效降低成本,提高效率,保证最佳质量,缩短交货周期,提升自主创新力。     

基于“新息误差”的粒子流滤波算法

在粒子滤波（PF）过程中存在粒子权值退化、维度灾难、计算成本高等问题。粒子流滤波通过构造对数同伦函数避免了粒子权值退化问题,但是在求解边值问题时过于依赖观测方程,当噪声较大时效果较差。针对上述问题,提出了一种改进的粒子流滤波算法。首先,该算法在粒子流动的过程中引入了一种“新息误差”结构,使每个粒子的更新相互独立;其次,利用Galerkin有限元法求得边值问题的数值解,从而消除了拟合样本先验可能导致的数值不稳定问题;最后,分别在通用非线性滤波模型和机动目标跟踪模型中对改进的算法进行了性能测试。仿真结果表明,改进的算法可以抑制系统对观测信息的依赖性,在噪声增大的情况下也能得到相对较好的结果,有效改善了滤波精度,而在多维目标跟踪情况下算法的计算效率与滤波精度高于标准粒子滤波。     

Innovative product design based on customer requirement weight calculation model

In the processes of product innovation and design, it is important for the designers to find and capture customer's focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.     

基于有限更新率的非带限信号采样与重建算法

针对Shannon采样定理中要求信号带宽有限的缺陷,提出了一种基于有限更新率的非带限信号采样和重建的方法.该方法借助奇异值分解技术,从空间变换的角度实现了对与狄拉克流有关的一类特殊有限更新率信号的采样与重建.它用采样点的离散傅里叶变换系数构成一个Hankel矩阵,通过对该矩阵进行奇异值分解求得狄拉克流的位置信息,然后再求解范德蒙方程组求取狄拉克流的权信息,重建出原信号.计算机仿真结果表明,只要以不低于信号更新率的速率对信号进行采样,利用该算法就可以准确地重建出原信号,而且具有很好的抗噪性能.     

面向知识服务的科技资源协同创新服务机制

在对知识即服务元模型进行定义与分析的基础上,提出了一个科技资源协同服务元模型STRCS,该模型包括科技资源模型、服务模型、协同模型3个子模型以及相应的科技资源与服务。同时,通过建立KAAS元模型与科技资源服务元模型间的映射机制,为科技资源平台中的知识服务模式提供了服务映射机制。在此基础上,进一步提出了一种面向KAAS的科技资源协同服务分类与知识聚合新机制,并针对动态多标签和动态文档索引的分类和聚合方式提出了优化的机制,以及科技资源的个性化服务与科技资源的知识协同机制;通过开发实现了一个基于社会化与知识服务化的科技资源公共服务平台,并利用算法优化提升了科技资源平台个性化推荐的能力与精确度,从而为解决科技资源协同创新和个性化知识服务的实施与集成提供了一个新方案。     

高职院校工学结合人才培养机制的创新与实践

为了推进工学结合、校企合作的人才培养模式改革,以创建国家示范性高职院校为实践平台,通过创新机制,在一定程度上解决了制约工学结合人才培养模式改革的主要问题。     

Performance Analysis of The Auxiliary‐Model‐Based Multi‐Innovation Stochastic Newton Recursive Algorithm for Dual‐Rate Systems

The stochastic Newton recursive algorithm is studied for dual‐rate system identification. Owing to a lack of intersample measurements, the single‐rate model cannot be identified directly. The auxiliary model technique is adopted to provide the intersample estimations to guarantee the recursion process continues. Intersample estimations have a great influence on the convergence of parameter estimations, and one‐step innovation may lead to a large fluctuation or even divergence during the recursion. In the meantime, the sample covariance matrix may appear singular. The recursive process would cease for these reasons. In order to guarantee the recursion process and to also improve estimation accuracy, multi‐innovation is utilized for correcting the parameter estimations. Combining the auxiliary model and multi‐innovation theory, the auxiliary‐model‐based multi‐innovation stochastic Newton recursive algorithm is proposed for time‐invariant dual‐rate systems. The consistency of this algorithm is analyzed in detail. The final simulations confirm the effectiveness of the proposed algorithm.