A secure communication method for a high-power information signal based on chaotic masking

In this paper,we present a secure communication method for a high-power information signal based on chaotic masking.In the transmitter,an adaptive controller is adopted to pick up the change of the information signal ,and to inject the controller‘s error into the transmitting system.At the same time,the information is directly added to the chaotic signal in transmission to drive the receiving system.In the receiver,another adaptive controller is used to maintain chaotic synchronization of the transmitting and receiving systems and to recover the information signal.Since the synchronization error is independent from the information signal,the power of the information signal can be equivalent to that of the chaotic signal,and the frequency of the information signal can be set within the range of the principal frequencies of the chaotic signal,The results of theoretical analysis and numerical simulation show that the presented method not only enhances the degree of security of low-dimensional chaotic systems but also significantly improves the signal-to-noise ratio at the receiving end.     

联合精确比值掩蔽与深度神经网络的单通道语音增强方法

针对目前有监督语音增强忽略了纯净语音、噪声与带噪语音之间的幅度谱相似性对增强效果影响等问题,提出了一种联合精确比值掩蔽(ARM)与深度神经网络(DNN)的语音增强方法。该方法利用纯净语音与带噪语音、噪声与带噪语音的幅度谱归一化互相关系数,设计了一种基于时频域理想比值掩蔽的精确比值掩蔽作为目标掩蔽;然后以纯净语音和噪声幅度谱为训练目标的DNN为基线,通过该DNN的输出来估计目标掩蔽,并对基线DNN和目标掩蔽进行联合优化,增强语音由目标掩蔽从带噪语音中估计得到;此外,考虑到纯净语音与噪声的区分性信息,采用一种区分性训练函数代替均方误差(MSE)函数作为基线DNN的目标函数,以使网络输出更加准确。实验表明,区分性训练函数提升了基线DNN以及整个联合优化网络的增强效果;在匹配噪声和不匹配噪声下,相比于其它常见DNN方法,本文方法取得了更高的平均客观语音质量评估(PESQ)和短时客观可懂度(STOI),增强后的语音保留了更多语音成分,同时对噪声的抑制效果更加明显。     

Effect of masking noise on cognitive performance and annoyance in open plan offices

Even for low noise levels, employees working in open-plan offices declare they are disturbed by different sound sources and especially by intelligible speech. This paper presents two experiments that aim at studying the effects of sound sources on task performance and cognitive load. In the first experiment, thirty-five individuals were assigned a serial memory task in four noise conditions: printers, intelligible speech, non-intelligible speech and phone rings. Noise annoyance was assessed by measuring task performance and cognitive workload (NASA-TLX). Although there was no significant difference between intelligible speech, unintelligible speech and phone ring tone signals in terms of annoyance, the performance in a memory task decreased in the presence of intelligible speech. In the second experiment, the relevance of a new intelligibility index was evaluated. This index was derived from eSII as defined by Rhebergen et al. (2006) to deal with fluctuating noise as speech babble. Fifty-five subjects performed a serial memory task in four STIt (time varying Speech Transmission Index calculated for every 12.5 ms in dynamic environment) conditions (from 0.38 to 0.69) while STI values were kept constant (around 0.36). No significant difference appeared between the decreases in performance observed with multiple levels of intelligibility. However, a significant difference between two groups of individuals appeared in performance measurements. The group of better performers seemed to be less affected by the high level of intelligibility condition than the other ones.     

Open-loop frequency response for a chaotic masking system

In this paper, a new numerical simulation approach is proposed for the study of open-loop frequency response of a chaotic masking system. Using Chua's circuit and the Lorenz system as illustrative examples, we have shown that one can employ chaos synchronization to separate the feedback network from a chaotic masking system, and then use numerical simulation to obtain the open-loop synchronization response, the phase response, and the amplitude response of a chaotic masking system. Based on the analysis of the frequency response, we have also proved that changing the amplitude of the exciting (input) signal within normal working domain does not influence the frequency response of the chaotic masking system. The new numerical simulation method developed in this paper can be extended to consider the open-loop frequency response of other systems described by differential or difference equations.     

噪声信号特征量分布函数相似特性的研究

应用高速数据采集卡,记录悬浮颗粒计数光电传感器本底噪声信号序列值,研究噪声信号独立特征量, 如信号幅度极值、上升沿幅值、下降沿幅值、极值时序间隔,以及特征量乘积值等统计分布规律. 结果表明,上述独立特征量均能够与以自然数l为自变量的对数正态分布函数高度符合, 噪声信号特征量统计分布呈现出高度相似特征.基于这种统计相似性,还可推出噪声信号不同特征量对应的统计自变量之间的幂函数变换关系.噪声信号特征量统计分布函数相似性可理解为噪声信号集合统计分形特性的一种表现.     

Using selective intensity and a HATS to evaluate noise sources in a car working at idle

Noise source ranking is required to make the noise level of a vehicle the lowest possible. That implies knowing the noise sources with the highest contribution to the total noise levels.Through the application of coherence techniques, the selective intensity can be defined as the portion of intensity that is coherent with a reference signal. Therefore, it is an effective way to determine the internal root causes of the emitted noise.In this paper, three experiments based on the selective intensity technique have been defined. The objective is observing the contributions of different noise sources of a vehicle, both outside and inside of it, when it is working at idle, and using as reference signals the two microphones of a HATS.With these experiments, it can be evaluated, on the one hand, the coherence between the intensity in the driver’s seat and external microphones located on both sides of the frontal axle of the car, in the exhaust and in the engine. On the other hand, it is evaluated the coherence between sound intensity in the same external points of the car and different positions of a HATS outside and inside of it; thus, as novelties the relation between the noise emitted by different parts of the vehicle and the noise perceived by the vehicle’s driver and by people located outside could be studied.     

Effect of adding artificial reverberation to speech-like masking sound

Time-reversed speech has been known to effectively mask information for speech privacy applications. However, the annoyance and distraction caused by the time-reversed speech-like masking sound is higher than other masking sound. This study investigates the effects of adding artificial reverberation to the time-reversed speech. Subjective listening tests have been conducted to measure the intelligibility of target speech, annoyance and distraction caused by the masking sound. The experimental results suggest that adding artificial reverberation to a speech-like masking sound has a significant effect to reduce the annoyance level while maintaining the masking effectiveness of the original masking sound. A trend was also observed that the addition of artificial reverberation could reduce the level of distraction caused by the masking sound.     

Background babble in open-plan offices: A natural masker of disruptive speech?

Numerous studies have shown that task-irrelevant background speech impairs performance of verbal short-term memory. This well-established effect is related to practice in open-plan offices, where employees are potentially disturbed by the speech of their colleagues. One option to reduce the disruptive effect is by masking the speech, for example, using random noise. Based on past research by Jones and Macken (1995), the ISO Standard 3382-3 (2012) assumes that multiple background speakers in open-plan offices may mask each other in a natural way, consequently reducing the disruptive effect of speech. The aim of this study was to check this assumption using a realistic acoustical simulation of an open-plan office situation. A combination of a nearby speaker and a varying number of background speakers was played to 26 participants while they performed on a verbal short-term memory task. Additionally, the intelligibility of the presented speaker sentences, levels of annoyance, and workload were checked. The results show a significant trend towards an improvement of short-term memory performance when the number of babble voices grows from one to six. However, performance levels are far from those reached under silent conditions. Moreover, annoyance and measures of subjective workload did not diminish due to babble masking.     

Selection of meaningless steady noise for masking of speech

This paper focuses on masking speech with meaningless steady noise as a way of realizing a comfortable sound environment. As a basis for research, meaningless steady noise at minimum sound pressure levels for masking of male or female meaningful speech is considered, based on psychological experiments using a method of adjustment. From the results, band-limited pink noise can be selected as the most effective noise for masking of speech. In the case of speech with a lower sound pressure level, the sound pressure level of the meaningless steady noise needs to be a little higher.     

开放型办公室掩蔽语音环境下工作效率的客观评价方法

本文研究了开放型办公室中平稳噪声掩蔽语音环境下噪声可懂度的客观评价指标与工作效率之间的关系。文章通过对三种客观评价指标:Speech Transmission Index(STI),Perceptually Evaluation of Speech Quality(PESQ)和modified Normalized Covariance Method(mNCM)与专门设计的主观实验结果相对比,得到了该条件下客观评价指标与主观烦扰度和工作效率之间的关系。结果显示,客观评价指标与主观实验结果均具有较高的相关性,说明利用客观评价指标来预测、评估工作效率具有可行性。实验结果还初步揭示了噪声的语言可懂度和工作效率之间的变化规律:在噪声的语言可懂度的中间区域,工作效率变化显著;但噪声的语言可懂度高于一定值以后,工作效率趋于稳定。     

基于簇相似度的网络社团结构探测算法

社团结构对复杂系统的结构特性和动力学特性有重要影响.提出了一个度量社团相似度的模型,称为簇相似度.该模型能够度量两个社团的相似度大小,为研究社团间的作用机制提供帮助.而且基于该模型,设计了一个社团划分算法.算法采用层次聚类的思想,每次合并两个相似度最大的社团,并通过一个评价函数选择最优社团划分.数值实验以及与CNM,GN,EigenMod等主流算法做比较,表明本算法的精度和效率都比较高,尤其对于边密度较高的网络,性能非常理想.     

基于非线性相似度量方法研究中国季节划分

利用中国气象局1961—2008年752个站点的候平均气温、气压、相对湿度和降水量资料,运用候平均气温划分方法、非线性相似度量方法和季节内离差最优分割方法,对中国的四季进行了划分,并研究了中国四季起始时间的空间分布.用多要素构造了描述气候状态的变量,以气候状态在不同季节间的转折变化为切入点,并与传统季节划分方法进行了对比研究,验证了非线性相似度量方法的可行性,得到了以下研究结果:一是多要素比单一的温度要素更全面贴切地描述气候状态的变化,划分结果更体现出大气环流形势和大气活动中心等的季节变化;二是从气候状态转折角度考虑季节划分是可行的,揭示了季节转换时大气系统的调整和转折变化,体现了大气系统在季节内保持相对平稳的特征,在季节间发生较大的调整的观测事实. 关键词： 季节划分 非线性相似度量方法 季节内离差最优分割法     

Riccati-coupled similarity shock wave solutions for multispeed discrete Boltzmann models

We study nonstandard shock wave similarity solutions for three multispeed discrete Boltzmann models: (1) the square 8_i, model with speeds 1 and 2 with thex axis along one median, (2) the Cabannes cubic 14_i model with speeds 1 and 3 and thex axis perpendicular to one face, and (3) another 14_i, model with speeds 1 and 2. These models have five independent densities and two nonlinear Riccati-coupled equations. The standard similarity shock waves, solutions of scalar Riccati equations, are monotonic and the same behavior holds for the conservative macroscopic quantities. First, we determine exact similarity shock-wave solutions of coupled Riccati equations and we observe nonmonotonic behavior for one density and a smaller effect for one conservative macroscopic quantity when we allow a violation of the microreversibility. Second, we obtain new results on the Whitham weak shock wave propagation. Third, we solve numerically the corresponding dynamical system, with microreversibility satisfied or not, and we also observe the analogous nonmonotonic behavior.     

基于层间相似性的时序网络节点重要性研究

时序网络可以更加准确地描述节点之间的交互顺序和交互关系.结合多层耦合网络分析法,本文提出了基于节点层间相似性的超邻接矩阵时序网络节点重要性识别方法,与经典的认为所有层间关系为常数不同,层间关系用节点的邻居拓扑重叠系数进行度量.Workspace和Enrons数据集上的结果显示:相比经典的方法,使用该方法得到的Kendall’sτ值在各时间层上的平均提高,最高为17.72%和12.44%,结果表明层间相似性的度量对于时序网络的节点重要性度量具有十分重要的意义.     

Assessing the ability of chemical similarity measures to discriminate between active and inactive compounds

Summary A method for assessing the biological discriminating power of chemical similarity measures is presented. The main concern of this work was to develop an objective way of evaluating different similarity measures in terms of how well they distinguished between active and inactive compounds. In addition, we have explored the level of similarity required for optimal separation and commented on its implications for work in the field of chemical diversity studies. The results for one simple similarity measure showed that statistically significant separation could be achieved, and indicated a reasonable similarity value for future work.     

Using metrics from complex networks to evaluate machine translation

Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems.     

Fourier transform method for self-mixing interference signal analysis

Self-mixing interferometry (SMI) has been used to measure the distance and displacement. Although the principle of self-mixing interference is different conventional interference, we concluded that FFT analysis technique could also be used to detect the signal phase and increase the measurement precision of self-mixing interferometry.First the SMI signal is obtained by feeding the light from the target to cavity of laser diode, then it is pre-processed by an analog subtraction circuit to remove the overlapped output intensity due to the injection current modulation. Finally, SMI signal is analyzed by FFT phase detection method. Theoretical analysis and simulation calculations are presented. Experimentally, displacement of a PZT-driven target was measured with a precision of λ/50.     

Simulating the effect of acoustic treatment types for residential balconies with road traffic noise

Development of design guides to estimate the difference in speech interference level due to road traffic noise between a reference position and balcony position or façade position is explored. A previously established and validated theoretical model incorporating direct, specular and diffuse reflection paths is used to create a database of results across a large number of scenarios. Nine balcony types with variable acoustic treatments are assessed to provide acoustic design guidance on optimised selection of balcony acoustic treatments based on location and street type. In total, the results database contains 9720 scenarios on which multivariate linear regression is conducted in order to derive an appropriate design guide equation. The best fit regression derived is a multivariable linear equation including modified exponential equations on each of nine deciding variables, (1) diffraction path difference, (2) ratio of total specular energy to direct energy, (3) distance loss between reference position and receiver position, (4) distance from source to balcony façade, (5) height of balcony floor above street, (6) balcony depth, (7) height of opposite buildings, (8) diffusion coefficient of buildings and (9) balcony average absorption. Overall, the regression correlation coefficient, R², is 0.89 with 95% confidence standard error of ±3.4 dB.     

利用时变全通滤波器减小扩声系统中的梳状滤波失真

根据人耳对声音信号相位不敏感的原理，采用时变全通滤波器，随机化每个声源输入信号的相位，从而减小声源输出信号之间的相关性，进而减小由于相关产生干涉而带来的梳状滤波失真。数值计算和实验结果均表明用时变全通滤波器随机化声源输入信号的相位能够有效地减小扩声系统中的梳状滤波失真。