A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

Kernel Spectral Matched Filter for Hyperspectral Imagery

In this paper a kernel-based nonlinear spectral matched filter is introduced for target detection in hyperspectral imagery, which is implemented by using the ideas in kernel-based learning theory. A spectral matched filter is defined in a feature space of high dimensionality, which is implicitly generated by a nonlinear mapping associated with a kernel function. A kernel version of the matched filter is derived by expressing the spectral matched filter in terms of the vector dot products form and replacing each dot product with a kernel function using the so called kernel trick property of the Mercer kernels. The proposed kernel spectral matched filter is equivalent to a nonlinear matched filter in the original input space, which is capable of generating nonlinear decision boundaries. The kernel version of the linear spectral matched filter is implemented and simulation results on hyperspectral imagery show that the kernel spectral matched filter outperforms the conventional linear matched filter.     

基于可重构FPGA技术的自适应FIR滤波器的实现

有限冲激响应(FIR)滤波器设计遇到的难题是滤波要进行大量乘法运算,即使是在全定制的专用集成电路中也会导致过大的面积与功耗.对于用硬件实现系数是常量的专用滤波器,可以通过分解系数变为应用加、减和移位而实现乘法.FIR滤波器的复杂性主要由用于系数乘法的加法器/减法器的数量决定.而对于自适应FIR滤波器,大多数场合下可用数字信号处理器(DSP)或CPU通过软件编程的方法来实现,但是对于要求高速运算的场合,VLSI实现是很好的选择.基于这一考虑,可以用符号数的正则表示(CSD)码表示系数, 再利用可重构现场可编程门阵列(FPGA)技术实现.可重构结构的应用,能保证系统的其余部分同时处于运行状态时实现FIR滤波器系数的更新.文中利用CSD码和可重构思想,提出了用FPGA实现自适应FIR滤波器的一种方案.     

WCDMA系统中SPT数字滤波器的一种设计方法

相对于传统的数字滤波器实现方法,符号的2次幂和(SPT)滤波器用移位寄存器替代乘法器,因而资源消耗少、速度快,更加适于专用集成电路(ASIC)设计.介绍了一种适用于宽带码分多址(WCDMA)前向信道中给定基带成形滤波器单位脉冲响应后设计SPT滤波器的方法.相对于传统的理想SPT系数优化方法,此方法更适于给定单位脉冲响应后SPT滤波器的设计,计算复杂度低;仿真结果显示,相对于更加简单的四舍五入方法,此算法在性能上又有可观的增益.     

基于频率采样技术的FIR数字滤波器优化设计

本文提出了一种FIR数字滤波器满意优化设计方法，将滤波器过渡带样本值作为优化变量，通过设计通带、过渡带和阻带性能指标满意度函数和综合满意度函数，构造出满意优化模型，并用本文提出的新量子遗传算法搜索满意解，FIR高通和带阻数字滤波器的设计结果表明，采用满意优化方法设计的FIR滤波器的性能优于传统方法。     

用Tow-Thomas电路设计含有限非零传输零点有源滤波器的方法

Tow-Thomas电路是一种实现全极点滤波器的典型电路。本文给出了用Tow-Thoms电路设计含有限非零传输零点有源滤波器的方法，从而使Tow-Thomas电路可用于单片集成滤波器电路。而文中给出的公式可用于计算外接元件。设计实例表明了文中给出的计算公式的正确性。     

介绍两种画中画插入播出器

介绍画中画插入播出器的工作原理及设计思想，并给出了实际的电原理图。     

自动线性跟踪Butterworth有源滤波器研究

滤波是通信、测试、数据采集和实时控制等领域至关重要的环节。通常的模拟滤波器，由于截止频率固定，在某些宽频率动态范围且有实时性要求的应用场合，往往达不到预期的滤波效果，有时甚至影响整个系统的正常运行。本文从有源滤波器的机理分析入手，提出了一种由单片机参与的滤波系统，它能自动跟踪输入信号频率，线性地选择合适的滤波器截止频率，弥补了原有滤波器的不足。     

新型微波有源滤波器综合方法

本文给出了一种新颖的微波有源滤波器的拓扑结构及综合方法，并对有源滤波电路进行了计算机模拟，结果表明本文给出的微波有源滤波器电路具有优良的的窄带滤波特性，通带内正向增益大于１０ｄＢ，带外抑制大于３０ｄＢ。