复数多值离散Hopfield神经网络的稳定性研究

本文提出了一个新的复数多电平离散Hopfield神经网络,构造了新的适用于复数多电平离散神经网的激活函数和能量函数,分别讨论了异步与同步更新模式下神经网的稳定性.该能量函数不仅能描述文献能量函数不适用的复数多值Hopfield神经网的动力学特性,而且能保证待盲检测信号位于能量函数的最小值点.为验证CMDHNN的有效性,利用本文特有的性能函数下所构造的联结权阵盲检测MQAM信号.仿真试验表明:本算法仅需较短接收数据就可有效盲检测MQAM星座信号,仿真也证明了CMDHNN能量函数全局最小值的稳定性推论. 关键词： 复数多电平离散Hopfield神经网络 盲检测 MQAM信号     

基于混沌神经网络的盲检测改进新算法

针对Hopfield神经网络的多起点问题,提出了一种新的基于混沌神经网络的盲信号检测算法,实现了二进制移相键控信号盲检测.据此进一步提出双sigmoid混沌神经网络模型,构造了新的能量函数,且证明了该模型的稳定性,并对网络参数进行配置.仿真实验表明:混沌神经网络能够避免局部极小点且具备较强的抗噪性能,双sigmoid混沌神经网络则继承了其所有的优点,且其收敛速度更快,仅需更短的接收数据即可到达全局真实平衡点,从而降低了算法的计算复杂度,减少了运行时间.     

连续多阈值神经元反馈神经网络盲检测光基带信号

空间分集接收可补偿信道衰落,提出了一种基于幅相联合激励法的连续多阈值神经元反馈神经网络(RNNCMVN)的光基带信号直接盲检测方法。针对多进制相移键控(MPSK)信号的特点,设计了两种连续相位多阈值激励函数形式,并简要讨论了该两类激励函数参数的选择;分别推演基于幅相联合激励法的RNNCMVN光基带信号盲检测方法工作于同步和异步两种模式下的新能量函数及其相关证明。同时针对正交调幅(QAM)信号的特点,分别设计出连续振幅和相位多阈值激励函数形式,最后通过仿真验证了该方法的有效性。     

光纤法布里-珀罗传感器幅值归一化-最小均方差联合解调算法

面向光纤法布里-珀罗传感器的腔长解调,提出一种结合幅值归一化与最小均方差的联合解调算法.采用幅值归一化实现返回光谱信号与模拟光谱信号的等幅,提高解调精度.仿真结果表明,相较于传统最小方差法,该算法的解调精度显著提升.实验结果表明,采用该算法可实现优于0.72nm的高分辨率.     

字典奇异值分解加权压缩感知多径信号参数估计

为提高水声信道多径参数估计的分辨率,提出了一种基于字典奇异值分解的加权压缩感知算法。对于有源声呐,根据发射信号构造字典,对字典进行奇异值分解,利用大特征值对应的特征向量构造信号子空间,然后使用信号子空间对接收信号进行滤波。对滤波结果进行加权压缩感知参数估计,得出最终时延估计结果。仿真实验表明,所提方法能够对水声多径参数进行超分辨估计,适用于任何脉冲信号。湖试处理结果显示,混响背景下该方法也有较好的多径参数估计性能,能够降低接收数据的噪声成分,提高对水声信道的多径时延、个数和幅度的估计精度。      

一种基于谱线幅值归零的加窗插值FFT谐波检测方法

提出了一种基于谱线幅值归零的加窗插值FFT谐波检测方法用于分析复杂电网信号中的各次谐波.该检测方法将每一次在离散频谱中找到的最大谱线及其左右两侧的数根谱线幅值归零,直到各次谐波分析完毕.通过仿真实验分析了在基波频率稳定时对模拟信号的测量精度,研究了基波频率波动对谐波分析的影响.通过对EAST实验数据的分析,验证了该谐波...     

电磁场中空间思维的构建

利用电子线路实验实现了用变量脉冲扰动法控制离散混沌 .该方法只用单一输出信号作为反馈信号 ,每隔一定的脉冲间隔将其加到系统的某些变量中去 ,适当调节脉冲间隔和反馈系数 ,可得到多个稳定的周期轨道 .该方法不仅适用于一维和二维离散系统 ,也适用于三维或更高维的离散系统 .     

声纹的变压器放电与机械故障诊断研究

变压器中的一些放电和机械故障会产生异常声,可用于故障检测.据此,该文提出基于可听声的变压器放电和机械故障诊断方法.针对机械故障声与变压器本体噪声特征相似易混淆的问题,提出改进小波包-BP神经网络算法,与传统小波包-BP神经网络算法相比声音识别率提高了5.7％.为提高声音识别系统的泛化性,提出基于梅尔对数频谱和卷积神经网...     

多胶接缺陷太赫兹检测信号的PSO-BP神经网络识别

采用太赫兹时域光谱无损检测技术对多胶接结构耐高温复合材料缺陷进行检测。为了识别同一位置上、下层同时存在脱粘缺陷,分析无缺陷区域、上层脱粘区域、下层脱粘区域的太赫兹信号波形,以特征峰峰度、偏度、最小值、峰谷值、波形因子以及信号幅值绝对平均值为特征,作为BP神经网络的输入。并通过粒子群算法优化BP神经网络的初始权重和阈值,解决了BP神经网络易陷入局部最优的问题。粒子群算法优化后的BP神经网络可实现上层100μm和下层100μm脱粘缺陷的识别,准确率达到90.71%和86.92%。     

提高基于机器视觉的心率测量精度的方法

基于摄像头(可见光)的心率测量方法,能够以非接触的方式检测受试者心率,无论在临床应用还是在家庭健康监护中都有着极大的应用前景。但是,CMOS摄像头的行扫描方式采集图像以及计算机系统的图像采集时钟抖动都会影响此类心率测量的精度,从而引入相位误差和系统随机误差。本文针对这两大主要误差进行研究分析,提出了消除相位误差的基于傅里叶变换的幅频叠加算法、消除图像采集系统时钟抖动误差的基于时间标定的三次样条插值重构方法。幅频叠加算法只在幅频域对信号进行处理,能够忽略信号的相位影响,从而消除相位误差。时间标定的三次样条重构算法能够重构图像的均匀采集,从而消除系统时钟抖动引起的随机误差。同时,通过理论推导论证了两种算法的可行性,进而利用LED模拟实验和实际心率测量实验验证该算法在提高信号检测精密度中的特性。在模拟实验中,对每帧图像的200行作幅频叠加运算,能够使信号幅值相对提升4.58%;基于时间标定的三次样条重构算法能使检测的信号频率的均方根误差缩小30%以上;在实际心率检测中,幅频叠加算法可使心率幅值相对提升达33.5%,基于时间标定的三次样条重构算法可使心率准确度提升40%左右。因此,模拟实验和实际心率测量实验均验证了提出的算法在提高系统检测精度上的有效性,提高了基于机器视觉心率测量的抗干扰能力。这两种算法不仅能够提高基于机器视觉的心率检测精度,而且能够适用于基于机器视觉对一定频率信号的检测,在机器视觉检测中具有广泛的意义。     

Internal tissue displacement measurement based on ultrasonic wave Doppler signal digital detection and its application to fetal movement monitoring

We have developed a fetal movement monitoring system based on small displacement measurement of internal tissues. When ultrasonic pulses are transmitted to the fetus, the reflected ultrasonic waves which have a Doppler frequency shift due to the fetal movements are detected by using an ultrasonic pulsed Doppler technique. In this paper, we propose a displacement measurement method for internal tissues which is based on the Doppler signal digital detection technique. In the method, the received ultrasonic RF signals are sampled with a sampling frequency of four times higher than the centre frequency of the ultrasonic waves; the Doppler frequency shift signals are derived using digital signal processing. From the detected signals, the internal displacements are estimated using the arc-tangent method. The basic algorithm of the detection method has already been used in the area of blood flow sensing, however, we apply the algorithm to the displacement measurement of internal tissues. The comparison between the proposed method and the conventional method is presented. The fetal movement quantitative monitoring system based on the method which has been constructed is shown.     

基于时频分析的多目标盲波束形成算法

针对现有盲波束形成算法适用范围较窄, 多目标信号分离级联模式结构复杂、并联模式稳定性较差等问题, 提出一种基于时频分析的多目标盲波束形成算法. 该算法首先利用时频分析技术给出信号导向矢量的不确定集, 然后优化求解导向矢量的最优估计, 最后利用Capon方法实现多目标信号的并行输出. 理论分析及仿真结果表明, 该算法对信号特性没有特殊要求, 适用性较广, 性能稳定, 且输出信干噪比高于其他盲波束形成算法, 接近于最优Capon波束形成器.     

信号在时变等离子体中的传播特性

高速飞行器等离子鞘套由于飞行姿态调整、湍流、非均匀烧蚀等因素的影响,使其等离子体参数存在时变特性,针对这种传输介质的快速时变特性引起的电波幅度、相位上的寄生调制效应,本文利用大面积辉光放电等离子体产生装置,搭建了等离子体中信号传输实验系统,进行了S频段的单频信号与调制信号传输实验,观测验证了调制效应的存在,且其调制频率与等离子体变化频率具有一致性,进一步分析了等离子参数与寄生调制效应的关系,理论和实验结果表明:即使当载波频率大于等离子频率时,时变等离子引起的寄生调制效应也会使传输信号的星座图发生旋转,造成其判决容差裕度变小,通信可靠性下降,并且载波频率越接近等离子频率时,其寄生调制效应越强烈。     

A blind algorithm for reverberation-time estimation using subband decomposition of speech signals

An algorithm for blind estimation of reverberation time (RT) in speech signals is proposed. Analysis is restricted to the free-decaying regions of the signal, where the reverberation effect dominates, yielding a more accurate RT estimate at a reduced computational cost. A spectral decomposition is performed on the reverberant signal and partial RT estimates are determined in all signal subbands, providing more data to the statistical-analysis stage of the algorithm, which yields the final RT estimate. Algorithm performance is assessed using two distinct speech databases, achieving 91% and 97% correlation with the RTs measured by a standard nonblind method, indicating that the proposed method blindly estimates the RT in a reliable and consistent manner.     

一种强噪声背景下微弱超声信号提取方法研究

为解决在强噪声背景下获取超声信号的难题,基于粒子群优化算法和稀疏分解理论提出一种强噪声背景下微弱超声信号提取方法.该方法将降噪问题转换为在无穷大参数集上对函数进行优化的问题,首先以稀疏分解理论和超声信号的结构特点为依据构建了粒子群优化算法运行所需要的目标函数及去噪后信号的重构函数,从而将粒子群优化算法和超声信号降噪联系在一起;然后根据粒子群优化算法可以在连续参数空间寻优的特点建立了用于匹配超声信号的连续超完备字典,并采用改进的自适应粒子群优化算法在该字典中对目标函数进行优化;最后根据对目标函数在字典上的优化结果确定最优原子,并利用最优原子按照重构函数重构出降噪后的超声信号.通过对仿真超声信号和实测超声信号的处理,结果表明本文提出的方法可以有效提取信噪比低至-4 dB的强噪声背景下的微弱超声信号,且和基于自适应阈值的小波方法相比本文方法表现出更好的降噪性能.     

Chaotic modulations and performance analysis for digital underwater acoustic communications

Two modulation schemes, M-ary phase shift keying (MPSK) and M-ary frequency shift keying (MFSK), are commonly used for coherent and incoherent digital communications, respectively. Despite wide applications in underwater acoustic (UWA) communications, they are not suitable for confidential applications for their well-known generating processes and signal features. In this paper, two corresponding chaotic modulation methods are proposed to improve their security, namely chaotic MPSK (CMPSK) and chaotic MFSK (CMFSK). By application of chaotic sequences into the modulation procedures, they can prevent the unauthorized receivers from extracting information from the intercepted signals even with high SNR. The confidential performance of chaotic modulations is evaluated by a designed automatic modulation classification (AMC) system. Simulation results indicate a success identification rate of more than 90% for the MPSK and MFSK signal at the SNR from −10 dB to 40 dB, but only an identification rate of nearly zero for the CMPSK and CMFSK signal. Therefore, chaotic modulations have lower available probability and can achieve higher confidential performance. Also, an experiment was conducted to verify the performance of chaotic modulations in actual UWA communications. The experimental results show that chaotic modulations can achieve similar bit error ratio (BER) compared with conventional digital modulations, which verifies potential applications of chaotic modulations in confidential UWA communications.     

Chaotic signal denoising algorithm based on sparse decomposition

Denoising of chaotic signal is a challenge work due to its wide-band and noise-like characteristics. The algorithm should make the denoised signal have a high signal to noise ratio and retain the chaotic characteristics. We propose a denoising method of chaotic signals based on sparse decomposition and K-singular value decomposition(K-SVD) optimization. The observed signal is divided into segments and decomposed sparsely. The over-complete atomic library is constructed according to the differential equation of chaotic signals. The orthogonal matching pursuit algorithm is used to search the optimal matching atom. The atoms and coefficients are further processed to obtain the globally optimal atoms and coefficients by K-SVD. The simulation results show that the denoised signals have a higher signal to noise ratio and better preserve the chaotic characteristics.