SIMO SC-FDE系统的CFR盲估计

提出了一种基于线性预测的单输入多输出单载波频域均衡系统频域信道响应(也称为信道频率响应,CFR)盲估计算法.与传统的线性预测时域信道估计方法不同,提出的算法不需要计算新息以及新息和输出序列的互相关,而是直接从预测滤波器系数获得频域信道响应估计的闭式解.算法仅采用输出序列的二阶统计量,对信道阶次过估计具有鲁棒性,并且估计性能优于传统的线性预测时域信道估计方法.计算机仿真结果验证了理论分析的正确性.     

无模型SISO时滞系统的PID参数稳定域研究

针对无精确模型的单输入单输出(SISO)时滞系统, 利用频率响应数据, 给出确定PID参数稳定域的解析方法. 首先通过继电反馈频域辨识法得到系统的频率响应数据, 然后基于该数据确定控制参数的奇异边界线和非奇异边界线, 并判断边界线的哪一侧具有更少的不稳定极点, 从而给出能使闭环系统稳定的控制参数区域. 该方法避免了模型辨识的复杂计算过程, 为无模型SISO时滞系统的PID控制器设计和调节提供了一条简单有效的途径. 仿真结果验证了方法的有效性.     

组合逻辑电路中软错误率的频域分析方法

基于频域的软错误率分析方法可实现快速而精确地分析组合逻辑中软错误的电气屏蔽特性和窗闩屏蔽特性.该方法利用信号和逻辑门的频域特性,计算瞬时错误信号在组合逻辑电路中传播过程.基于频域的分析方法主要分为2个处理步骤:线性系统处理和非线性系统处理.线性系统处理通过电路系统的频率响应来计算输出信号.非线性系统处理瞬时信号的幅度过...     

第八讲 测量系统的动态特性及其性能指标(二) 三、测量系统的频域性能指标

当被测信号是正弦函数或其它周期性函数时,用频域法来研究和分析测量系统的动态特性要比用时域法方便和准确得多。测量系统对被测量的频率响应是指系统对正弦输入的稳态响应。由于各种变化规律的输入量均可以通过富氏变换分解成一系列具有不对同频率和幅值的正弦信号,因此,频域法在原则上适用于任意变化规律的信号。测量系统的频率响应特性主要包括幅频特性、相频特性和幅相特性,其频域性能指标也主要从上述几个特性上来定义。     

随机模型的频域分析及辨识

本文证明了时间域内的平稳相关序列经离散傅里叶变换之后,听得到的是频域内的正交随机序列。因此,当系统的激励信号为确定性信号,而输出信号被平稳相关随机噪声所污染时,根据输入信号、输出信号的采样序列所得到的频率响应函数也是正交随机序列。利用方差的倒数加权进行最小二乘估计,可以得到系统连续模型参数的有效估计值。     

基于模型的数字音频广播信号调制系统设计

本文设计并在FPGA芯片中实现了数字音频广播系统的信号调制系统。信号调制系统位于整个数字音频广播系统基带信号处理链的末端,是基带数字信号处理的核心系统。根据Eureka 147标准,信号调制系统需要对输入的基带码流进行数字调制、频域交织、差分调制以及正交频分复用等一系列处理。所设计的信号调制系统能够对输入的基带码流进行实时处理,完成上述信号处理算法,并输出数字音频广播的基带信号。     

基子TMS320VC5410的三分量全光纤加速度检波器数字信号处理系统

介绍了用于地震勘探工作中的三分量全光纤加速度检波器数字信号处理系统.该系统以高性能的TMS320VC5410为核心,辅以必要的外围电路,实现了对加速度信号的高精度检测.测试结果表明,检波器数字信号处理系统在共振频率以上有较好的频率响应,输入信号与输出信号吻合较好.     

基于TMS320VC5410的三分量全光纤加速度检波器数字信号处理系统

介绍了用于地震勘探工作中的三分量全光纤加速度检波器数字信号处理系统。该系统以高性能的TMS320VC5410为核心,辅以必要的外围电路,实现了对加速度信号的高精度检测。测试结果表明,检波器数字信号处理系统在共振频率以上有较好的频率响应,输入信号与输出信号吻合较好。     

多输入系统变结构控制的一种新方法

给出了多输入系统变结构控制的一种新方法，把多输入系统滑动模态的构造转化为单输入系统，用输出动态反馈和频域技巧配置动模态极点，保证了系统有较好的动态性能。最后用实例说明了方法的有效性。     

质子交换膜燃料电池模型的频域分数阶子空间辨识

针对质子交换膜燃料电池(PEMFC)系统发电过程中的分数阶特性, 本文提出了一种频域分数阶子空间辨 识方法建立PEMFC的分数阶状态空间(FOSS)模型. 考虑到时域分数阶的微分形式计算复杂度较大, 将时域中的分 数阶微分在频域中转化为乘积的形式. 首先, 采用随机多频正弦激励信号对时域采集的信号进行处理, 得到输入输 出的频率响应数据; 其次, 利用频率响应数据构造实、虚部矩阵; 接着, 通过RQ分解、SVD分解以及最小二乘法求取 系统系数矩阵A, B, C, D; 由于参数同元分数阶次α、辅助阶次q以及频域采样点数M未知, 本文提出了一种GA– PSO算法进行优化, 将PSO算法作为主线, 加入GA算法中的选择、交叉和变异操作, 以进一步提高个体的自适应调 整搜索方向、增强全局寻优的能力. 仿真结果验证了算法的有效性, 频域分数阶子空间辨识方法得到的输出能够较 好的跟随实测数据, 且优化后的辨识结果误差更小, 精确度更高, 能够更准确地描述PEMFC的电特性变化过程.     

基于瞬时频率响应函数的间歇过程时段划分

多时段特性是间歇过程的本质特性之一,对间歇过程实现有效的时段划分是故障监测的基础。传统的时段划分方法大多针对过程的输入输出数据,对输入输出数据突变较为敏感。本文提出一种基于瞬时频率响应函数的间歇过程时段划分方法,该方法基于系统的瞬时动态特性,用瞬时频率响应函数替代输入输出数据进行时段划分,利用小波变换估计系统的瞬时频率响应函数进行核主元分析降维,通过模糊C均值聚类对降维后频率响应函数进行聚类划分时段。实验结果表明,本文所提出的方法能够实现对间歇过程的时段划分,并具有较高的鲁棒性。     

具有输入约束和输出噪声的不确定系统级联线性自抗扰控制EI北大核心CSCD

针对一类具有输入约束和输出噪声的SISO(Single input single output)不确定非线性系统,提出了一种基于误差补偿和工程滤波的抗饱和级联线性自抗扰控制(Linear active disturbance rejection control,LADRC)方法.首先针对高频量测噪声,分析了线性扩张状态观测器(Linear extended state observer,LESO)对噪声的放大机理及其与观测器增益的定量关系,进而设计了一种基于工程滤波器的级联LADRC方法,在滤除噪声的同时有效补偿了因滤波所造成的输出幅值和相位损失,确保了闭环系统的跟踪精度.然后继续考虑输入饱和的问题,利用LADRC的实时估计/补偿能力,通过将饱和差值信号引入LESO,设计了一种基于误差补偿的抗饱和LADRC方法,有效减小了系统设计控制量,避免了系统长时间陷入饱和.通过实时仿真比较,验证了所提出方法的有效性.     

Weak, stochastic temporal correlation of large scale synaptic input is A major determinant of neuronal bandwidth

We determine the bandwidth of a model neurone to large-scale synaptic input by assessing the frequency response between the outputs of a two-cell simulation that share a percentage of the total synaptic input. For temporally uncorrelated inputs, a large percentage of common inputs are required before the output discharges of the two cells exhibit significant correlation. In contrast, a small percentage (5%) of the total synaptic input that involves stochastic spike trains that are weakly correlated over a broad range of frequencies exert a clear influence on the output discharge of both cells over this range of frequencies. Inputs that are weakly correlated at a single frequency induce correlation between the output discharges only at the frequency of correlation. The strength of temporal correlation required is sufficiently weak that analysis of a sample pair of input spike trains could fail to reveal the presence of correlated input. Weak temporal correlation between inputs is therefore a major determinant of the transmission to the output discharge of frequencies present in the spike discharges of presynaptic inputs, and therefore of neural bandwidth.     

Discrete time subharmonic modelling and analysis

Traditionally the Volterra time and frequency domain analysis tools cannot be applied to severely non-linear systems. In this paper, a new method of building a time-domain NARX MISO model for a class of severely SISO non-linear systems that exhibit subharmonics is introduced and it is shown how this allows the Volterra time and frequency domain analysis to be extended to this class of non-linear systems. The new approach is based on decomposing the original single input based on a Fourier analysis to provide a set of modified input signals which have the same period as the output signal. A MISO NARX model can then be constructed from the decomposed multiple inputs and the single output signal. The resulting MISO model is shown to meet the basic requirement for the existence of a Volterra series representation from which important frequency domain properties can be derived, explained and discussed. This is done by first introducing the derivation of generalized frequency response functions (GFRFs) from time domain MISO NARX models. The steady state response synthesis problem using the input spectrum and the MISO GFRFs is then investigated in order to verify the effectiveness and accuracy of the MISO modelling approach for severely non-linear systems. Finally a new frequency domain analysis method is introduced for systems that exhibit subharmonic oscillations.     

Design of input signals for parameter estimation

The optimum energy-constrained and time-constrained input signal is obtained for estimating the parameters of a system. The output is corrupted by nonstationary, nonwhite additive observation noise, and the observation time is finite. The reproducing kernel Hilbert space formulation is used to obtain the parameter estimates and the error covariance matrix in terms of the input. The performance index, assumed to be a function of the error covariance matrix, is minimized by a variational procedure. A necessary condition for optimality is that the input satisfy a nonlinear Fredholm equation. An example estimates the gain of a single time constant system where the observation noise has an exponential autocorrelation function. For broadband noise, the optimum input is a portion of a sinusoid. For a noise bandwidth narrower than the system bandwidth, the optimum input switches sign as rapidly as possible, but near-optimum performance can be obtained with a relatively high frequency sinusoidal input.     

高性能计算机总线变换器输出阻抗优化设计

针对中间母线架构分布式供电的高性能计算机电源稳定性问题,详细分析了三种不同控制方法总线变换器的输出阻抗特性,给出了负载点变换器输入阻抗低频值和总线变换器输出阻抗峰值的计算公式。建立了由一个总线变换器和两个负载点变换器组成的实验电路,对总线变换器输出阻抗进行了优化设计,并实际测量了输入和输出阻抗,验证了理论分析的正确性。实验和应用结果表明,输出阻抗优化设计可以有效解决高性能计算机电源稳定性问题。     

多输入多输出系统的数据分层建模

为了高效准确地实现多输入多输出系统的数据建模,本文提出了数据分层建模算法.将多输入多输出数据建模问题分解为一系列单输入多输出的建模问题,同时改进标准遗传编程算法,将单树表示的的个体结构扩展为向量树的进化个体,实现多输出系统的自动建模.通过大量的计算实例表明,这种算法可以实现复杂的多输入多输出系统的建模,提高数据建模的效率和精度.     

Output frequency response characteristics of nonlinear systems. Part II: overlapping effects and commensurate multi-tone excitations

The output response of nonlinear systems is strongly dependent on the extent to which different input frequency combinations/intermodulations overlap one another and contribute to a common output frequency component. This makes it hard to determine the actual number of output frequencies, or to determine which of the many possible combinations contribute to a specified output frequency of interest. Systematic algorithms are presented for resolving these issues in a manner, which is both efficient and straightforward to implement on a computer. Three broad classes of input are considered: multi-tone, but nominally incommensurate sinusoids; multi-tone, harmonically related sinusoids and multi-tone excitations that are equi-spaced in frequency. The considered inputs also admit the possibility of a dc bias component since this can significantly affect the system response. The algorithms are therefore applicable to a broad range of practical inputs, and their use and benefits are illustrated with several examples.     

Identification of frequency domain models for nonlinear systems

This paper presents a computer-aided engineering approach for identification of linear models from a set of frequency response data. The approach is based on a new system identification technique. The primary intention of the developed system identification technique and the associated software is to identify linear models for nonlinear systems whose input/output behaviour is characterized by their corresponding sinusoidal-input describing function models. However, the technique may also be applied to identification of linear models from experimental frequency response data. At present, the identification approach and the associated software is limited to single-output, linear, deterministic, and time-invariant systems. A computer-aided engineering environment based on the developed system identification technique has also been developed. The software is developed on a Harris-800 super-minicomputer and a Tektronix 4115B high resolution, raster, and color graphics terminal.