Consistency property of extended least-squares parameter estimation for stochastic diffusion equation

The extended least-squares parameter estimate for stochastic heat diffusion equations is considered. The unknown parameter is a heat diffusion coefficient which is a function of a spatial variable. Almost sure convergence for the estimated parameter is proved. A numerical example is demonstrated for supporting the theoretical results developed here.     

电力系统同调机群的识别方法

在对电力系统中同调机群的识别方法进行研究的同时，并对以往的各种同调机群的识别方法也进行了归纳总结，针对这些方法所存在的问题，给出了一种新的较为实用的同调机群识别方法。     

国际工程项目承包中招标方法研究

根据概率和数理统计分析，提出工程项目招标方法中的模拟技术，给出不同招标方法的比较研究结果。     

语音合成库的建立与汉语数码语音识别途径

利用语音合成芯片 TC8830 AF的 CPU控制方式下的 DMA功能 ,主控微机可共享语音数据存储器 SRAM资源 ,对语音数据直接操作 ,实现语音数据的快速处理 ,对语音合成库的建设机理进行了深入探讨 ,并提出了一种实用的汉语数码语音识别方法 .实践结果表明本系统适用于语音合成产品的开发     

Monitoring of multivariable dynamic processes and sensor auditing

Industrial continuous processes are usually operated under closed-loop control, yielding process measurements that are autocorrelated, cross correlated, and collinear. A statistical process monitoring (SPM) method based on state variables is introduced to monitor such processes. The statistical model that describes the in-control variability is based on a canonical variate (CV) state space model. The CV state variables are linear combinations of the past process measurements which explain the variability of the future measurements the most, and they are regarded as the principal dynamic dimensions. A T² statistic based on the CV state variables is utilized for developing the SPM procedure. The CV state variables are also used for monitoring sensor reliability. An experimental application to a high temperature short time (HTST) pasteurization process illustrates the proposed methodology.     

基于小波逼近和尺度变换的非参数辨识方法

提出一种以非正交小波为基函数并应用小波多尺度分析的系统脉冲响应辨识方法，该方法以小波级数的形式逼近脉冲响应过程．从理论上证明了经小波尺度变换后系统随机噪声的方差值减小，即噪声得到有效的抑制，从而大大提高了辨识精度．应用实例验证了所得结果的正确性和算法的实用性．     

冗余度机器人运动模型的神经网络辨识及实现

为提高网络学习速度,提出了一种新的动态神经网络结构——状态延迟输入动态递归神经网络.以德国PowerCube^TM模块化机器人为研究对象,将机器人系统返回的关节位置信息和OPTOTRAK30203维运动测量系统测得的机器人末端位置信息作为神经网络的学习样本,对包含各种影响因素的机器人运动模型进行了辨识,所得结果及误差分析,说明了SDIDRNN在学习能力上的优越性.     

A framework for determining design correctness

Quality is one of the main concerns in today's systems and software development and use. One important instrument in verification is the use of formal methods, which means that requirements and designs are analyzed formally to determine their relationships. Furthermore, since professional software design is to an increasing extent a distributed process, the issue of integrating different systems to an entity is of great importance in modern system development and design. Various candidates for formalizing system development and integration have prevailed, but very often, particularly for dynamic conflict detection, these introduce non-standard objects and formalisms, leading to severe confusion, both regarding the semantics and the computability. In contrast to such, we introduce a framework for defining requirement fulfillment by designs, detecting conflicts of various kinds as well as integration of heterogeneous schemata. The framework introduced transcends ordinary logical consequence, as it takes into account static and dynamic aspects of design consistency and, in particular, the specific features of the state space of a specification. Another feature of the approach is that it provides a unifying framework for design conflict analysis and schema integration.     

Modelling and FDI of Dynamic Discrete Time Systems Using a MLP with a New Sigmoidal Activation Function

In this paper we investigate the use of the multi-layer perceptron (MLP) for system modelling. A new sigmoidal activation function is introduced and the study is focused at the utilization of this function on a MLP that performs modelling of dynamic, discrete time systems. The role of the activation function in the training process is investigated analytically, and it is proven that the shape of the activation function and it's derivative can affect the training outcome. The method is simulated at a well known benchmark, namely the three tank system, and is incorporated in a Fault Detection and Identification (FDI) method, also applied and simulated at the three tank system. Finally, a comparison is made with an approach that utilizes local model neural networks for system modeling.     

一种改进的PIV互相关算法

本文在对两种传统PIV算法进行深入分析的基础上，融合了它们的优点而发展了一种新的速度提取算法一预估搜索法，并给出了算法的具体实现步骤。人工及真实图像实验均表明该法具有求解速度快、计算精度高的优点。