An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles

This paper proposes an adaptive filter-based method for detection and frequency estimation of whistle calls, such as the calls of birds and marine mammals, which are typically analyzed in the time-frequency domain using a spectrogram. The approach taken here is based on adaptive notch filtering, which is an established technique for frequency tracking. For application to automatic whistle processing, methods for detection and improved frequency tracking through frequency crossings as well as interfering transients are developed and coupled to the frequency tracker. Background noise estimation and compensation is accomplished using order statistics and pre-whitening. Using simulated signals as well as recorded calls of marine mammals and a human whistled speech utterance, it is shown that the proposed method can detect more simultaneous whistles than two competing spectrogram-based methods while not reporting any false alarms on the example datasets. In one example, it extracts complete 1.4 and 1.8 s bottlenose dolphin whistles successfully through frequency crossings. The method performs detection and estimates frequency tracks even at high sweep rates. The algorithm is also shown to be effective on human whistled utterances.     

Captive dolphins,Tursiops truncatus,develop signature whistles that match acoustic features of human-made model sounds

This paper presents a cross-sectional study testing whether dolphins that are born in aquarium pools where they hear trainers' whistles develop whistles that are less frequency modulated than those of wild dolphins. Ten pairs of captive and wild dolphins were matched for age and sex. Twenty whistles were sampled from each dolphin. Several traditional acoustic features (total duration, duration minus any silent periods, etc.) were measured for each whistle, in addition to newly defined flatness parameters: total flatness ratio (percentage of whistle scored as unmodulated), and contiguous flatness ratio (duration of longest flat segment divided by total duration). The durations of wild dolphin whistles were found to be significantly longer, and the captive dolphins had whistles that were less frequency modulated and more like the trainers' whistles. Using a standard t-test, the captive dolphin had a significantly higher total flatness ratio in 9/10 matched pairs, and in 8/10 pairs the captive dolphin had significantly higher contiguous flatness ratios. These results suggest that captive-born dolphins can incorporate features of artificial acoustic models made by humans into their signature whistles.     

一种精确检测未知弱复合周期信号频率的非线性融合方法

研究了信号经随机共振器后所产生的奇倍频现象，巧妙获得了混沌检测子的参考频率，由混沌检测子的“频率选择性”滤除了其中的虚假频率. 关键词： 弱复合周期信号 随机共振 奇倍频现象 混沌相变     

Performance of a contour-based classification method for whistles of Mediterranean delphinids

Whistles from five delphinid species in the western Mediterranean Sea (Stenella coeruleoalba, Grampus griseus, Delphinus delphis, Tursiops truncatus, Globicephala melas) were taken from GREC sound archives. FFT contours (window size 512, Hanning, sampling frequency 44.1 kHz) were extracted with custom developed Matlab software: 277 samples of striped dolphins (Sc), 158 whistles of Risso’s dolphins (Gg), 120 of common dolphins (Dd), 76 of bottlenose dolphins (Tt), and 66 of pilot whales (Gm) were selected. Seafox software extracted 15 variables from the digitized contours, including: duration, initial, final, maximal and minimal frequency slopes, frequency range, number of frequency extrema, beginning, ending, maximal and minimal frequencies, presence of harmonics. Four of five species were significantly different (Mann-Whitney test) for average durations (respectively 0.73, 0.65, 0.47 and 0.89 s for Sc, Gg, Dd, Gm) while the average duration of bottlenose dolphins was 0.71 s. Frequency ranges (respectively 7.3, 6.3, 4.6, 3.2 and 6.3 kHz) were significantly different for all species pairs, with the exception of bottlenose and Risso’s dolphins. From a global point of view, pilot whale calls were the most distinct, with 43 significant pair-wise tests out of a total of 52, followed by the common dolphins. Risso’s dolphins were closest to other species whistles. A CART classification method achieved a global classification rate of 62.9%.     

Spectrogram denoising and automated extraction of the fundamental frequency variation of dolphin whistles

Marine mammal vocalizations are often analyzed using time-frequency representations (TFRs) which highlight their nonstationarities. One commonly used TFR is the spectrogram. The characteristic spectrogram time-frequency (TF) contours of marine mammal vocalizations play a significant role in whistle classification and individual or group identification. A major hurdle in the robust automated extraction of TF contours from spectrograms is underwater noise. An image-based algorithm has been developed for denoising and extraction of TF contours from noisy underwater recordings. An objective procedure for measuring the accuracy of extracted spectrogram contours is also proposed. This method is shown to perform well when dealing with the challenging problem of denoising broadband transients commonly encountered in warm shallow waters inhabited by snapping shrimp. Furthermore, it would also be useful with other types of broadband transient noise.     

A novel interferometric method for contour mapping of optically rough surfaces

A new white light interferometric arrangement for contour mapping of light diffusing but not depolarising surfaces is presented and compared with related electronic speckle and holographic interferometry (ESPI and HI) methods. Using two angles of illumination of the tested surface, and modifying the light beam in the observation pupil it is possible to observe contour fringes with arbitrary sensitivity depending on the geometry of a chosen set-up.     

A method for classifying whistles of bottlenose dolphin(Tursiops truncates) based on syntactic pattern reorganization

A method based on syntactic pattern recognition was presented to automatically classify whistles of bottlenose dolphin.Dolphin whistles have typically been characterized in terms of their instantaneous frequency as a function of time,which is also known as "whistle contour".The frequency variation features of a whistle were extracted according to its contour.Then,the frequency variation features were used for learning grammatical patterns.A whistle was classified according to grammatical pattern of its frequency variation features.The experimental results showed that the classification accuracy of the proposed method was 95%.The method can provide technical support for acoustic study of dolphins' biological behavior.     

A tool for real-time acoustic species identification of delphinid whistles

The ability to identify delphinid vocalizations to species in real-time would be an asset during shipboard surveys. An automated system, Real-time Odontocete Call Classification Algorithm (ROCCA), is being developed to allow real-time acoustic species identification in the field. This Matlab-based tool automatically extracts ten variables (beginning, end, minimum and maximum frequencies, duration, slope of the beginning and end sweep, number of inflection points, number of steps, and presence/absence of harmonics) from whistles selected from a real-time scrolling spectrograph (ISHMAEL). It uses classification and regression tree analysis (CART) and discriminant function analysis (DFA) to identify whistles to species. Schools are classified based on running tallies of individual whistle classifications. Overall, 46% of schools were correctly classified for seven species and one genus (Tursiops truncatus, Stenella attenuata, S. longirostris, S. coeruleoalba, Steno bredanensis, Delphinus species, Pseudorca crassidens, and Globicephala macrorhynchus), with correct classification as high as 80% for some species. If classification success can be increased, this tool will provide a method for identifying schools that are difficult to approach and observe, will allow species distribution data to be collected when visual efforts are compromised, and will reduce the time necessary for post-cruise data analysis.     

Segregation of concurrent sounds. II: Effects of spectral envelope tracing, frequency modulation coherence, and frequency modulation width

The research presented here concerns the simultaneous grouping of the components of a vocal sound source. McAdams [J. Acoust. Soc. Am. 86, 2148-2159 (1989)] found that when three simultaneous vowels at different pitches were presented with subaudio frequency modulation, subjects judged them as being more prominent than when no vibrato was present. In a normal voice, when the harmonics of a vowel undergo frequency modulation they also undergo an amplitude modulation that traces the spectral envelope. Hypothetically, this spectral tracing could be one of the criteria used by the ear to group components of each vowel, which may help explain the lack of effect of frequency modulation coherence among different vowels in the previous study. In this experiment, two types of vowel synthesis were used in which the component amplitudes of each vowel either remained constant with frequency modulation or traced the spectral envelope. The stimuli for the experiment were chords of three different vowels at pitch intervals of five semitones (ratio 1.33). All the vowels of a given stimulus were produced by the same synthesis method. The subjects' task involved rating the prominence of each vowel in the stimulus. It was assumed that subjects would judge this prominence to be lower when they were not able to distinguish the vowel from the background sound. Also included as stimulus parameters were the different permutations of the three vowels at three pitches and a number of modulation conditions in which vowels were unmodulated, modulated alone, and modulated either coherently with, or independently of, the other vowels. Spectral tracing did not result in increased ratings of vowel prominence compared to stimuli where no spectral tracing was present. It would therefore seem that it has no effect on grouping components of sound sources. Modulated vowels received higher prominence ratings than unmodulated vowels. Vowels modulated alone were judged to be more prominent than vowels modulated with other vowels. There was, however, no significant difference between coherent and independent modulation of the three vowels. Differences among modulation conditions were more marked when the modulation width was 6% than when it was 3%.     

A novel method for detecting light source for digital images forensic

Manipulation in image has been in practice since centuries. These manipulated images are intended to alter facts — facts of ethics, morality, politics, sex, celebrity or chaos. Image forensic science is used to detect these manipulations in a digital image. There are several standard ways to analyze an image for manipulation. Each one has some limitation. Also very rarely any method tried to capitalize on the way image was taken by the camera. We propose a new method that is based on light and its shade as light and shade are the fundamental input resources that may carry all the information of the image. The proposed method measures the direction of light source and uses the light based technique for identification of any intentional partial manipulation in the said digital image. The method is tested for known manipulated images to correctly identify the light sources. The light source of an image is measured in terms of angle. The experimental results show the robustness of the methodology.     

一种基于频率方差加权的线谱目标检测方法

在复杂的多目标声场中,常规波束形成（CBF）检测器性能显著下降。本文提出一种基于频率方差加权的线谱目标检测方法——CBF频率方差检测器,利用被动目标辐射噪声中含有高强度的稳定线谱这一特征,用每个方位频率域的峰值频率方差对CBF输出的方位谱进行加权。该检测器可在多目标强干扰和同波束强相干干扰背景中检测到弱线谱目标,且只须三维显示,避开了传统的线谱检测四维显示的难点。仿真和海试结果表明,在多目标、强干扰的环境下,可以探测到弱线谱目标。     

A detecting method for line-spectrum target based on variance-of-frequency weight

There are highly intensive and stable line-spectrums in the radiated noise of passive target,and different targets have line-spectrums with different frequencies.This paper puts forward Conventional BeamForming(CBF) variance-of-frequency detector,which weights bearing spectrum using the variance of frequency of line spectrum with maximum amplitude in each azimuth. It is able to suppress multi-target interferences effectively,and detect faint signal in the background of strong interferences.What’s more,CBF variance-of-frequency detector needs only three-dimension display,while other line-spectrum detectors require for four-dimension display.The simulation and trial data analysis show that the CBF variance-of-frequency detector is able to detect faint line-spectrum target in the background of the continuous spectrum strong interferences.     

一种新型的空气扰动探测方法

基于光折变材料的二波耦合特性提出了一种新型的空气扰动探测方法。空气中的微扰导致入射到光折变材料中两束光的光程差发生改变，干涉条纹随之发生变化。由于光折变体相位栅建立时间比较长，体相位栅不能及时跟随干涉条纹发生变化，导致干涉条纹与体相位栅间的相移将随空气扰动信息的变化而变化。相移角的改变将导致瞬态能量转移，输出两束光的能量在瞬态能量转移作用下将实现对空气扰动信息的光调制，并且这种调制过程是一种差分调制方式。在接收端采用电差分检测方法便可解调出空气扰动信息。这种利用光折变体相位栅的差分探测方法在未来的探测领域将有广泛的应用前景。     

一种宽吻海豚通讯信号自动分类的方法

针对宽吻海豚通讯信号自动分类提出了一种基于句法模式识别的方法。该方法首先提取海豚通讯信号基频随时间变化的轨迹曲线,然后提取基频变化的基元序列。根据海豚通讯信号分类的标准,归纳出产生各类海豚通讯信号基频基元序列的文法。对未知类别的海豚通讯信号,提取其基频变化的基元序列,根据各类模式的文法对基元序列进行分类,进而实现海豚通讯信号的自动分类。实验结果显示本文方法的分类准确率达到了95%。本文方法预期为海豚生物学行为的声学研究提供一定的技术支持。     

A new method for detecting pulse gamma ray with scattered electrons

This paper describes a newly designed gamma pulse detector of current mode that uses the scattered electron method. Tungsten is used as the scattering target, an organic thin film scintillator ST401 is used to collect the scattered electrons. The spatial distribution of the electronic energy-flux density is studied by using the MCNP code. The optimization of the target and the thickness of the scintillator are also discussed. The results indicate that the energy response is relatively flat in the range of 0.4 to 5 MeV.     

A heuristic method for identifying chaos from frequency content

The sign of the largest Lyapunov exponent is the fundamental indicator of chaos in a dynamical system. However, although the extraction of Lyapunov exponents can be accomplished with (necessarily noisy) the experimental data, this is still a relatively data-intensive and sensitive endeavor. This paper presents an alternative pragmatic approach to identifying chaos using response frequency characteristics and extending the concept of the spectrogram. The method is shown to work well on both experimental and simulated time series.     

Time and frequency parameters of bottlenose dolphin whistles as predictors of surface behavior in the Mississippi Sound

In this study, an algorithm previously developed for estimating the total ultrasonic attenuation along the propagation path from the surface of the transducer to a region of interest (ROI) in tissue, was modified to make it more practical for use in clinical settings. Specifically, the algorithm was re-derived for when a tissue mimicking phantom rather than a planar reflector is used to obtain the reference power spectrum. The reference power spectrum is needed to compensate for the transfer function of the transmitted pulse, the transfer function of transducer, and the diffraction effects that result from focusing/beam forming. The modified algorithm was tested on simulated radio frequency (RF) echo lines obtained from two samples that have different scatterer sizes and different attenuation coefficient slopes, one of which was used as a reference. The mean and standard deviation of the percent errors in the attenuation coefficient estimates (ACEs) were less than 5% and 10%, respectively, for ROIs that contain more than 10 pulse lengths and more than 25 independent echo lines. The proposed algorithm was also tested on two tissue mimicking phantoms that have attenuation coefficient slopes of 0.7 dB/cm-MHz and 0.5 dB/cm-MHz respectively, the latter being the reference phantom. When a single element spherically focused source was used, the mean and standard deviation of the percent errors in the ACEs were less than 5% and 10% respectively for windows that contain more than 10 pulse lengths and more than 17 independent echo lines. When a clinical array transducer was used, the mean and standard deviation of the percent errors in the ACEs were less than 5% and 25%, respectively, for windows that contain more than 12 pulse lengths and more than 45 independent echo lines.     

A new method for frequency calibration and control of a laser

A new method is introduced for high-precision measurement of the wavenumber of monochromatic radiation emitted by a single-mode tunable laser. The main task of the apparatus (called sigmameter) is the direct measurement of the wave-number. Furthermore it serves as a reference for the stabilization and piloting of the laser frequency.     

A novel local PCA-based method for detecting activation signals in fMRI.

A novel local principal component analysis (LPCA) technique is presented for activation signal detection in functional magnetic resonance imaging (fMRI) without explicit knowledge about the shape of the model activation signal. Unlike the traditional PCA methods, our LPCA algorithm is based on a measure of separation between two clusters formed by the signal segments in active periods and inactive periods, which is computed in an eigen-subspace. In addition, we only applied PCA to the temporal sequence of each individual voxel instead of applying PCA to the fMRI data set. In our algorithm, we first applied a linear regression procedure to alleviate the baseline drift artifact. Then, the baseline-corrected temporal signals were partitioned into active and inactive segments according to the paradigm used for the fMRI data acquisition. Principal components were computed from all these segments for each voxel by PCA. By projecting the segments of each voxel onto a linear subspace formed by the corresponding most dominant principal components, two separate clusters were formed from active and inactive segments. An activation measure was defined based on the degree of separation between these two clusters in the projection space. We show experimental results on the activation signal detection from various sets of fMRI data with different types of stimulation by using the proposed LPCA algorithm and the standard t-test method for comparison. Our experiments indicate that the LPCA algorithm in general provides substantial signal-to-noise ratio improvement over the t-test method.