A model of acoustic transmission in the respiratory system

A theoretical model of sound transmission from within the respiratory tract to the chest wall due to the motion of the walls of the large airways was developed. The vocal tract, trachea, and the first five bronchial generations are represented over the frequency range from 100 to 600 Hz by an equivalent acoustic circuit. This circuit allows the estimation of the magnitude of airway wall motion in response to an acoustic perturbation at the mouth. The radiation of sound through the surrounding lung parenchyma is represented as a cylindrical wave in a homogeneous mixture of air bubbles in water. The effect of thermal losses associated with the polytropic compressions and expansions of these bubbles by the acoustic wave is included and the chest wall is represented as a massive boundary to the wave propagation. The model estimates the magnitude of acceleration over the extrathoracic trachea and at three locations on the posterior chest wall in the same vertical plane. The predicted spectral characteristics of transmission are consistent with previous experimental observations. This theoretical approach suggests that the locations of the spectral peaks are a strong function of the geometry and the wall properties of the airways, while the attenuation at higher frequencies is primarily associated with the absorption of sound in the parenchyma.     

Nonlinear cepstral equalisation method for noisy speech recognition

The authors deal with the problem of automatic speech recognition in the presence of additive white noise. The effect of noise is modelled as an additive term to the power spectrum of the original clean speech. The cepstral coefficients of the noisy speech are then derived from this model. The reference cepstral vectors trained from clean speech are adapted to their appropriate noisy version to best fit the testing speech cepstral vector. The LPC coefficients, LPC derived cepstral coefficients, and the distance between test and reference, are all regarded as functions of the noise ratio (the spectral power ratio of noise to noisy speech). A gradient based algorithm is proposed to find the optimal noise ratio as well as the minimum distance between the test cepstral vector and the noise adapted reference. A recursive algorithm based on Levinson-Durbin recursion is proposed to simultaneously calculate the LPC coefficients and the derivatives of the LPC coefficients with respect to the noise ratio. The stability of the proposed adaptation algorithm is also addressed. Experiments on multispeaker (50 males and 50 females) isolated Mandarin digits recognition demonstrate remarkable performance improvements over noncompensated method under noisy environment. The results are also compared to the projection based approach, and experiments show that the proposed method is superior to the projection approach under a severe noisy environment     

A method for the acoustical analysis of respiratory crackles in cryptogenic fibrosing alveolitis

Crackles are impulsive sounds occurring in particular pulmonary diseases. This note presents the preliminary results of a study on the acoustical characteristics of crackles, particularly in cryptogenic fibrosing alveolitis, for the purpose of determining the diagnostic effectiveness of such a merely acoustic technique.     

A method for the analysis of respiratory sinus arrhythmia using continuous wavelet transforms

A continuous wavelet transform-based method is presented to study the nonstationary strength and phase delay of the respiratory sinus arrhythmia (RSA). The RSA is the cyclic variation of instantaneous heart rate at the breathing frequency. In studies of cardio-respiratory interaction during sleep, paced breathing or postural changes, low respiratory frequencies, and fast changes can occur. Comparison on synthetic data presented here shows that the proposed method outperforms traditional short-time Fourier-transform analysis in these conditions. On the one hand, wavelet analysis presents a sufficient frequency-resolution to handle low respiratory frequencies, for which time frames should be long in Fourier-based analysis. On the other hand, it is able to track fast variations of the signals in both amplitude and phase for which time frames should be short in Fourier-based analysis.     

一种TD-LTE系统上行干扰三维分析方法

TD-LTE上行干扰水平是评估网络质量的重要指标,当网络受到上行干扰时,上行吞吐量、尤其是小区边缘用户的上行吞吐量将受到影响,干扰严重时甚至会影响用户的接入性能。本文对TD-LTE系统上行干扰问题进行研究,提出干扰频域、时域及地理分布特征三维联合分析方法,实现了TD-LTE系统上行干扰的全方位分析,可大大提高TD-LTE干扰优化与排查工作的效率及准确性。     

Detection of landmines and underground utilities from acoustic and GPR images with a cepstral approach

This paper introduces a cepstral approach for the automatic detection of landmines and underground utilities from acoustic and ground penetrating radar (GPR) images. This approach is based on treating the problem as a pattern recognition problem. Cepstral features are extracted from a group of images, which are transformed first to 1-D signals by lexicographic ordering. Mel-frequency cepstral coefficients (MFCCs) and polynomial shape coefficients are extracted from these 1-D signals to form a database of features, which can be used to train a neural network with these features. The target detection can be performed by extracting features from any new image with the same method used in the training phase. These features are tested with the neural network to decide whether a target exists or not. The different domains are tested and compared for efficient feature extraction from the lexicographically ordered 1-D signals. Experimental results show the success of the proposed cepstral approach for landmine detection from both acoustic and GPR images at low as well as high signal to noise ratios (SNRs). Results also show that the discrete cosine transform (DCT) is the most appropriate domain for feature extraction.     

一种新的改善激光声信号特性的方法

为了改善激光声信号的特性,设计了激光声换能器。对换能器的设计原理和结构进行了说明。构建了激光声实验系统,利用脉冲激光分别在自由场和换能器内部聚焦击穿水介质产生声信号,由水听器将声信号转换成电信号并送入数字存储示波器。对两种条件下产生的激光声信号特性进行了比较。结果表明:同自由场产生的激光声信号相比,利用换能器产生的激光声信号特性有了一定程度的改善。其中,信号峰值幅度提高了3 倍,能量向60 kHz 以下频段集中,1m处发散角压缩到13.2,衰减速度变慢。     

倒谱域特征分量置信度分析及说话人识别应用

缺失数据理论的置信度分析用于说话人识别时,使用的是滤波器组语音特征,虽然系统的鲁棒性可以提高,但整体的误识率依然很高。为了进一步降低系统的误识率,本文在滤波器组语音特征分量置信度的基础上,提出了一种用于计算倒谱域特征MFCC各维分量置信度的方法CBTM,该方法通过一个置信度变换矩阵,估算出经过Mel谱减法处理后的MFCC各维分量的置信度,在此基础上通过对GMM模型的方差加权来减少置信度小的特征分量对输出概率的影响,以此来提高系统的鲁棒性。在基于SUDA2002语料库的说话人辨认实验中,上述方法对NoiseX 92噪声库中的white、pink、factory1噪声表现出了比传统方法更低的误识率,说明了这种方法的有效性。      

A high-sensitivity real-time acoustic imaging system for biomedical diagnosis

A real-time acoustic imaging system which is essentially the acoustic equivalent of the scanning electron-beam microscope is proposed. This system with piezoelectric detection is superior in theoretical performance to all the presently existing systems. A possible embodiment of such a system is described.     

一种前视阵列SAR系统的天线设计和分析方法

阵元数太多导致前视阵列SAR系统天线成本高和设计复杂,如何以较少的阵元数获取较高的成像质量是前视阵列SAR系统面临的重难点问题.根据系统成像质量要求,结合波束扫描、栅瓣抑制等技术,本文提出一种稀疏收发天线阵的设计方法.理论分析和仿真实验结果表明,该方法在保证一定成像质量的前提下,有效降低了阵元数量,提高了系统信噪比,具有一定的应用价值.     

Numerical analysis of two-dimensional piezoelectric waveguides for surface acoustic waves by finite-element method

A combined approach of the finite-element method and the analytical solutions is described for the analysis of two-dimensional piezoelectric waveguides with semi-infinite media for surface acoustic waves. Agreement between the exact and predicted results is very good.     

A comparative approach between cepstral features for human authentication using heart sounds

The main objective of this paper is to provide a comparative study between different cepstral features for the application of human recognition using heart sounds. In the past 10 years, heart sound, which is known as phonocardiogram, has been adopted for human biometric authentication tasks. Most of the previously proposed systems have adopted mel-frequency and linear frequency cepstral coefficients as features for heart sounds. In this paper, two more cepstral features are proposed. The first one is based on wavelet packet decomposition where a new filter bank structure is designed to select the appropriate bases for extracting discriminant features from heart sounds. The other is based on nonlinear modification for mel-scaled cepstral features. The four cepstral features are tested and compared on two databases: One consists of 21 subjects, and the other consists of 206 subjects. Based on the achieved results over the two databases, the two proposed cepstral features achieved higher correct recognition rates and lower error rates in identification and verification modes, respectively.     

A wavelet transform based contrast enhancement method for underwater acoustic images

Multidimensional Systems and Signal Processing - Dredging the surface of the ocean to identify both living and non living things nowadays has become an unproblematic task with the help of the...     

An acoustic model of the respiratory tract

With the emerging use of tracheal sound analysis to detect and monitor respiratory tract changes such as those found in asthma and obstructive sleep apnea, there is a need to link the attributes of these easily measured sounds first to the underlying anatomy, and then to specific pathophysiology. To begin this process, we have developed a model of the acoustic properties of the entire respiratory tract (supraglottal plus subglottal airways) over the frequency range of tracheal sound measurements, 100 to 3000 Hz. The respiratory tract is represented by a transmission line acoustical analogy with varying cross sectional area, yielding walls, and dichotomous branching in the subglottal component. The model predicts the location in frequency of the natural acoustic resonances of components or the entire tract. Individually, the supra and subglottal portions of the model predict well the distinct locations of the spectral peaks (formants) from speech sounds such as /a/ as measured at the mouth and the trachea, respectively, in healthy subjects. When combining the supraglottic and subglottic portions to form a complete tract model, the predicted peak locations compare favorably with those of tracheal sounds measured during normal breathing. This modeling effort provides the first insights into the complex relationships between the spectral peaks of tracheal sounds and the underlying anatomy of the respiratory tract.     

A complete system for on-line 3D modelling from acoustic images

This paper presents a system for the three-dimensional (3D) reconstruction of an underwater environment on the basis of multiple range views from an acoustical camera. The challenge is to provide the reconstruction on-line, as the range views are obtained from the sensor. The final target of the work is to improve the understanding of a human operator driving an underwater Remotely Operated Vehicle. The acoustic camera provides a sequence of 3D images in real time. Data must be registered and fused to generate a unique 3D mosaic in the form of a triangle mesh, which is rendered through a graphical interface. Available technologies for registration and meshing have been modified and extended to match time constraints. Some experiments on real data are reported.     

On analysis method for infrared multi-sites system performance

The calculation method about infrared multi-sites passive system location is introduced based on the principle of the weighted least square method, and the variance matrix of estimated error is offered. Through deduction, it can be found out that treated appraise precision can be directly analyzed and deduced without carrying out real measure and reaching estimation value. The simulation result shows that the system performance based on the weighted least square method is much better than the traditional passive location method, and it can be also used for reference to the research of the location algorithm of similar system.     

A model selection method for nonlinear system identification based FMRI effective connectivity analysis

In this paper a model selection algorithm for a nonlinear system identification method is proposed to study functional magnetic resonance imaging (fMRI) effective connectivity. Unlike most other methods, this method does not need a pre-defined structure/model for effective connectivity analysis. Instead, it relies on selecting significant nonlinear or linear covariates for the differential equations to describe the mapping relationship between brain output (fMRI response) and input (experiment design). These covariates, as well as their coefficients, are estimated based on a least angle regression (LARS) method. In the implementation of the LARS method, Akaike's information criterion corrected (AICc) algorithm and the leave-one-out (LOO) cross-validation method were employed and compared for model selection. Simulation comparison between the dynamic causal model (DCM), nonlinear identification method, and model selection method for modelling the single-input-single-output (SISO) and multiple-input multiple-output (MIMO) systems were conducted. Results show that the LARS model selection method is faster than DCM and achieves a compact and economic nonlinear model simultaneously. To verify the efficacy of the proposed approach, an analysis of the dorsal and ventral visual pathway networks was carried out based on three real datasets. The results show that LARS can be used for model selection in an fMRI effective connectivity study with phase-encoded, standard block, and random block designs. It is also shown that the LOO cross-validation method for nonlinear model selection has less residual sum squares than the AICc algorithm for the study.     

Design and evaluation of optimal cepstral lifters for accessingarticulatory codebooks

It is noted that of great importance to the success of the articulatory approach to speech coding is the use of a good distortion measure between a given speech signal and the entries in a stored codebook of impulse responses and corresponding vocal-track shapes (articulatory codebook). One promising distortion measure is the weighted cepstral distortion. Since the impulse responses in the articulatory codebook do not include glottal characteristics, the authors derive optimal weighting functions (cepstral lifters) to reduce the influence of a varying glottal source on the cepstral distortion measure. This is done by examining the ensemble of cepstral coefficients of speech produced by an articulatory speech synthesizer that also includes a vocal-cord model. The obtained cepstral lifters are optimal for the given ensemble of cepstral coefficients and for given constraints on the weighting function. They are different for cepstral coefficients derived from the power spectrum (FFT cepstra) and for those derived from LPC (linear predictive coding) coefficients (LPC cepstra). The performances of the obtained cepstral lifters are compared in an articulatory codebook search