利用CMOS门电路检测信号阈值

本文提出了一种新的利用CMOS门电路测定信号阈值的方法,避开了CMOS门电路线性区的影响,使CMOS门电路可以广泛用于信号阈值的测量中。

智能光模块中可变阈值的信号丢失检测电路

采用CSMC0.6μm2P2MCMOS工艺设计并实现了一种新型可用于智能光模块的可变阈值信号丢失(LOS)检测电路,电路利用光接收机中的限幅放大器组成准对数律接收信号强度指示电路.该指示电路与迟滞比较器、基准参考源、运算放大器和两个外部调节电阻组成了可变报警阈值的LOS检测电路.整个电路工作于5V单电源供电,功耗为60mW.测试结果表明,对于155Mbps的输入信号,信号检测的动态范围高达60dB,对数精度小于2dB.可变报警阈值范围为1～700mV,同时保证报警迟滞宽度为4dB左右.良好的性能预示了该电路潜在的商业前景.

舰船无线网络入侵干扰信号优化检测方法分析

为全面提升舰船无线网络的耐候感受能力,提出一种新型的入侵干扰信号优化检测方法。通过信号阈值选取、识别函数确定2个操作环节,完成舰船无线网络入侵干扰信号的精准识别。在此基础上,通过信号目标定位、连续检测波形确定、检测脉冲量计算3个步骤,完成新型舰船无线网络入侵干扰信号优化检测方法分析。对比实验结果表明,与普通方法相比,应用优化检测方法后,入侵干扰信号的平均波长降至3.0×10-11 Hz以下,最佳定位精准度可突破90%,舰船无线网络的耐候感受能力得到稳定提升。

拉曼光谱仪噪声阈值实时计算方法研究

通过分析拉曼光谱仪谱图信号,利用噪声本身固有的无规则上下频繁跳动的特性,提出了一种快速简易的噪声阈值实时计算方法,该方法通过设置窗口信号上下跳动次数阈值来识别噪声信号段与谱峰信号段或奇异信号段,再对所提取的噪声信号段通过线性回归最终获得噪声阈值。经理论分析和仿真实验结果证明该算法是一种灵活实用、快速简易的高效算法。

基于改进北斗卫星导航的超高层建筑变形监测方法

针对当前超高层建筑变形监测方法存在建筑基线分量计算误差大、无法提供明确建筑变形信息的问题,提出基于改进北斗卫星导航的超高层建筑变形监测方法.通过计算超高层建筑图像的信号阈值,获取图像噪声强度等信息,完成图像信息去噪.在去噪图像基础上,根据误差计算公式获取建筑总投点的误差以及总体高度,并构建变形监测模型.通过对该模型的计算,实现了超高层建筑变形监测.结果表明,所提方法的超高层建筑基线分量误差较小,并具备较高的误差校准能力,验证了所提方法的有效性.

改善超声波气体流量计测量精度的方法研究

超声波流量计是工业检测领域重要测量仪表,其检测精度的提高是一个很有价值的研究热点。从声时差测量和流场特性分析着手,分析信噪比、阈值对声时差检测的影响对超声换能器信号加以调试,从流场修正系数相对雷诺数的经验值分析管道结构和换能器安装位置对测量精度的影响,提出相应效率高成本低的改善方法。

通过切换算法提高AODV协议的性能

在A d Hoc网络中,节点的频繁移动导致链路经常失效,AODV路由协议对失效链路反应速度过慢,使网络中报文丢失率增加以及端到端平均传递时延增长。为了解决这个问题,文章提出了一种路由切换的算法。使活动路由中的每个节点收到数据报文时估算链路的状态,如果发现正在使用的链路即将失效,则节点在链路失效前将相关路由信息切换到合适的节点上。通过ns-2对增加切换算法的AODV协议进行仿真,结果表明,在节点移动的情况下,改进后的算法明显提高了AODV协议的报文投递率,降低了端到端平均传递时延,而路由开销仅有少量的增加。

Application of wavelet package filtering in the de-noising of fiber optic gyroscopes

To reduce the drift error existing in the output signal of fiber optic gyroscopes （FOG）, a mathematical model of the FOG output signal is set up; the error characteristics of the FOG output signal are analyzed, and semi-soft threshold filtering is chosen based on the comparison of hard threshold and soft threshold filtering. The semi-soft threshold wavelet package filtering method is applied in the filtering of the FOG output signal. Experiments of the stationary and dynamic FOG output signals filtered with the wavelet package analysis are carried out in a lab environment, respectively. Experiments done with the real-time measured FOG signal show that the method of semi-soft threshold wavelet package filtering reduces the mean square error from 5 （°）/h to 1 （°）/h, so it is effective in eliminating the white noises and the fractal noises existing in the FOG. The novel method proposed here is proved valid in reducing the FOG drift error, satisfying the technical demands of high precision and realtime processing.

基于PID优化的卧式数控车床电气自动控制系统

针对传统数控车床控制系统信号响应速率较慢、超调量较大的问题,提出设计基于PID优化的卧式数控车床电气自动控制系统。利用PID技术结合电气自动控制系统中脉冲信号阈值、过电流系数,构建数控车床中直电流传递函数,采用比例、微分调控、实际参数积分三种调节机制,计算自动控制程序的参数差值,利用积分法模拟替代差值,使数据差值逐渐逼近实际数值。通过总体控制方案、控制电路、数控工作台和自动急停装置的设计,组成完整的自动控制系统。实验结果表明,所提系统控制信号响应率及准确性较高,可实现有效的电气自动控制。

Denoising Method for Shear Probe Signal Based on Wavelet Thresholding

Shear probe works under a tough environment where the turbulence signals to be measured are very weak. The measured turbulence signals often contain a large amount of noise. Due to wide frequency band, noise signals cannot be effectively removed by traditional methods based on Fourier transform. In this paper, a wavelet thresholding denoising method is proposed for turbulence signal processing in that wavelet analysis can be used for multi-resolution analysis and can extract local characteristics of the signals in both time and frequency domains. Turbulence signal denoising process is modeled based on the wavelet theory and characteristics of the turbulence signal. The threshold and decomposition level, as well as the procedure of the turbulence signal denoising, are determined using the wavelet thresholding method. The proposed wavelet thresholding method was validated by turbulence signal denoising of the Western Pacific Ocean trial data. The results show that the propsed method can reduce the noise in the measured signals by shear probes, and the frequency spectrums of the denoised signal correspond well to the Nasmyth spectrum.

Implementation of Adaptive Wavelet Thresholding Denoising Algorithm Based on DSP

By utilizing the capability of high-speed computing,powerful real-time processing of TMS320F2812 DSP,wavelet thresholding denoising algorithm is realized based on Digital Signal Processors.Based on the multi-resolution analysis of wavelet transformation,this paper proposes a new thresholding function,to some extent,to overcome the shortcomings of discontinuity in hard-thresholding function and bias in soft-thresholding function.The threshold value can be abtained adaptively according to the characteristics of wavelet coefficients of each layer by adopting adaptive threshold algorithm and then the noise is removed.The simulation results show that the improved thresholding function and the adaptive threshold algorithm have a good effect on denoising and meet the criteria of smoothness and similarity between the original signal and denoising signal.

A continuous differentiable wavelet threshold function for speech enhancement

Enhanced speech based on the traditional wavelet threshold function had auditory oscillation distortion and the low signal-to-noise ratio (SNR). In order to solve these problems, a new continuous differentiable threshold function for speech enhancement was presented. Firstly, the function adopted narrow threshold areas, preserved the smaller signal speech, and improved the speech quality; secondly, based on the properties of the continuous differentiable and non-fixed deviation, each area function was attained gradually by using the method of mathematical derivation. It ensured that enhanced speech was continuous and smooth; it removed the auditory oscillation distortion; finally, combined with the Bark wavelet packets, it further improved human auditory perception. Experimental results show that the segmental SNR and PESQ (perceptual evaluation of speech quality) of the enhanced speech using this method increase effectively, compared with the existing speech enhancement algorithms based on wavelet threshold.

Stochastic Resonance in a Simple Threshold Sensor System with Alpha Stable Noise

We investigate the effect of alpha stable noise on stochastic resonance in a single-threshold sensor system by analytic deduction and stochastic simulation. It is shown that stochastic resonance occurs in the threshold system in alpha stable noise environment, but the resonant effect becomes weakened as the alpha stable index decreases or the skewness parameter of alpha stable distribution increases. In particular, for Cauchy noise a nonlinear relation among the optimal noise deviation parameter, the signal amplitude and the threshold is analytically obtained and illustrated by using the extreme value condition for the output signal-to-noise ratio. The results presented in this communication should have application in signal detection and image restoration in the non-Gaussian noisy environment.