多通带线性相移滤波器的数字仿真及其应用

本文利用数字仿真定理［１］，设计了多通带线性相移模拟滤波器的数字系统，探讨了设计原则和步骤，并依此编写了Ｃ语言通用设计软件，给出了设计实例与应用实例     

一种阵列信号超分辨率快速算法

提出了一种阵列信号超分辨率快速算法，并分析了它的收敛速度。这种算法基于协方差矩阵的特征值平移和矩阵的幂迭代，而不需要矩阵求逆。它的收敛速度快，一般只需几次迭代就能收敛，且算法结构简单，易于实现。     

连续小波变换在机械故障定位检测中的应用

本文从实用角度介绍连续小波变换的主要特性。实例表明在故障定位检测中，其性能优于谱分析，ＡＲ（Ｐ）建模及匹配滤波。     

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.     

Combining classifiers: A theoretical framework

The problem of classifier combination is considered in the context of the two main fusion scenarios: fusion of opinions based on identical and on distinct representations. We develop a theoretical framework for classifier combination for these two scenarios. For multiple experts using distinct representations we argue that many existing schemes such as the product rule, sum rule, min rule, max rule, majority voting, and weighted combination, can be considered as special cases of compound classification. We then consider the effect of classifier combination in the case of multiple experts using a shared representation where the aim of fusion is to obtain a better estimate of the appropriatea posteriori class probabilities. We also show that the two theoretical frameworks can be used for devising fusion strategies when the individual experts use features some of which are shared and the remaining ones distinct. We show that in both cases (distinct and shared representations), the expert fusion involves the computation of a linear or nonlinear function of thea posteriori class probabilities estimated by the individual experts. Classifier combination can therefore be viewed as a multistage classification process whereby thea posteriori class probabilities generated by the individual classifiers are considered as features for a second stage classification scheme. Most importantly, when the linear or nonlinear combination functions are obtained by training, the distinctions between the two scenarios fade away, and one can view classifier fusion in a unified way.     

Sensor Fusion System Using Recurrent Fuzzy Inference

In robotic and manufacturing systems, it is difficult to measure the state of systems accurately because of many uncertain factors and noise, and it is very important to estimate the state of systems. We must measure the phenomena of systems by multiple sensors and estimate the state of systems by acquiring information of sensors. However, we can not acquire all of sensor information synchronically, because each sensor has particular sensor information and measuring time. For estimating the state of systems by multiple sensors, a multi-sensor fusion system fusing various sensory information is needed. In this paper, we propose a Recurrent Fuzzy Inference (RFI) with recurrent inputs and apply it to a multi-sensor fusion system for estimating the state of systems. The membership functions of RFI are expressed by Radial Basis Function (RBF) with insensitive ranges. The shape of the membership functions can be adjusted by a learning algorithm. The learning algorithm is based on the steepest descent method and incremental learning which can add new fuzzy rules. The effectiveness of the multi-sensor fusion system using RFI will be shown through a numerical experiment of moving robot and estimation of surface roughness in grinding process.     

小信号检测中间歇混沌运动的机理􀀁

讨论了小劝的受迫Ｄｕｆｆｉｎｇ振子在非平衡相变临界点附近的行动，推导出振子发生相奕的相位条件，得出在该临界点附近相奕对小信号敏感的结论，推导出系统发生间歇混沌现象的频差条件，该临界点附近的微小左是产生间歇混沌的原因，这是与切分岔概念不同的产生间歇混沌的又一机理。     

高速PCB设计技术

高速ＰＣＢ已成为数字系统设计中的主流设计。本文概述了ＰＣＢ设计的发展趋势及设计流程，详细分析了影响高速信号传输的关键因素，具体介绍了规则驱动的ＰＣＢ设计方法和高速ＰＣＢ设计分析技术，介绍了现代ＥＤＡ技术的概况。     

冲击波场高速数据采集系统

介绍了一种测试瞬态冲击波压力场的３２通道高速采集及实时处理系统。设计了由Ｉｎｔｅｌ４８６和ＤＳＰ（数字信号处理器）构成的三级ＣＰＵ分布系统，解决了多通道采样同步、自动触发、数据传输阻塞、实时处理等高速采集中的常见问题，为冲击波等瞬态信号的测试提供了一种切实可行的方法。由于采用了模块化设计思想，该系统的采集处理部分能够单独做为一套通用测试设备。     

一种飞行模拟转台专用信号发生器

介绍一种为三轴飞行模拟转台控制系统的调试和检验而设计的基于单片微机的数字信号发生器，该数字式信号发生器的主要特点在于能同时产生两路相关的函数信号，用于产生飞行模拟转台控制系统所需的位置给定和速度给定信号，十分便于基于复合控制实现频率特性校正的飞行模拟转台控制系统的应用。