Chair: Boulalem Boashash, Q.U.T., Signal Processing Research Centre (AUSTRALIA)
Gema Pinero, Universidad Politecnica de Valencia (SPAIN)
Luis Vergara, Universidad Politecnica de Valencia (SPAIN)
We present in this paper a new interdisciplinary application of digital signal processing and its result in comparison with the application of classical methods. The problem is the separation of two acoustic waves propagating along an exhaust pipe. It has been proved that the use of the array signal processing technique - signals are registered by an array of sensors placed along the pipe and processed by means of the LCMV beamformer - has achieved very good results under bad conditions as the uncertainty in the speed propagation knowledge. The array technique has also been applied to the separation of two pressure waves generated by the discharge of a fuel injection pump. In this case results have been good but a preprocessing must be done due to the pulse character of these pressure waveforms.
Detlef Konig, Ruhr University Bochum (GERMANY)
Christian Tork, Ruhr University Bochum (GERMANY)
Johann F. Bohme, Ruhr University Bochum (GERMANY)
For adaptive control of modern car engines the combustion process has to be observed. Direct measurement of cylinder pressure is costly and not suitable for implementation. Therefore, we approximate the pressure by appropriate filtering of one or more vibration signals that can be measured easily. It has been shown that the pressure signal can be modelled as second order cyclostationary (SOSC). The transfer characteristic between pressure and vibration is time-varying due to the motion of the piston during observation. Therefore, for constant rotation speed we assume a linear periodic time-varying model. In this case, pressure and vibration signals are jointly SOCS. Based on this we formulate the optimum filter problem for our application. Solutions for this problem are known from the literature. We choose an appropriate one, adapt it to our problem and estimate the filter parameters. A real data experiment demonstrates the quality of this estimation.
A.M. Oroujeh, University of Illinois at Chicago (USA)
W. O'Neill, University of Illinois at Chicago (USA)
A.P. Keegan, University of Illinois at Chicago (USA)
S.L. Merritt, University of Illinois at Chicago (USA)
The human pupillary light reflex has long been studied as a typical biological nonlinear system. We have used a sinusoidal non-harmonic signal as the input light stimulus and pupil diameter as the output of the system. A recursive least square method is then used to estimate the measured pupil diameter in terms of the input light. With a good estimate, the underlying dynamical behavior of the system would be captured by the estimated parameters. Thus we modeled the estimated parameters as ARIMA processes. Then the residual noise associated with the ARIMA models was examined and revealed that people with narcolepsy had considerably lower sum-square-error than people without this sleep disorder (controls). This method turns out to be a relatively simple and fast test procedure for narcolepsy discrimination.
P. Poignet, Universite de Nantes
M. Guglielmi, Universite de Nantes
B. Vozel, Universite de Nantes
I. Richard, Hopital Saint-Jacques (FRANCE)
The purpose of this paper is the presentation of the results of a comparative study of the respective efficiency of three parametric signal processing methods to detect abrupt spectral changes by means of the detection of abrupt model discontinuities, while they were applied to the very particular case of inspection of change in myoelectric activity of surface electromyograms (E.M.G.). The studied surface electromyograms are those of biceps brachii during a perturbed flexion-extension forearm movement in the horizontal plane. After the description of the experimental device, the problem position is then formally considered, and the different used methods are briefly recalled. Finally, the results observed on a large set of trials are showed to light the behaviour of each selected method before concluding on the opportunity to use them to characterize some neuropathies.
Mark Roessgen, Queensland University of Technology (AUSTRALIA)
Boualem Boashash, Queensland University of Technology (AUSTRALIA)
This paper considers the problem of seizure detection in the neonate based on electroencephalogram (EEG) data. It will be shown that by using a histologically and biophysically justifiable model for the generation of the EEG, the detection of electrographic seizure is greatly improved. The model is presented along with an estimator for the model parameters. Then a simple seizure detection scheme based on the model parameter estimates is suggested. It is shown that this scheme is superior in performance to spectral analysis techniques such as the periodogram when used to analyse both simulated and real EEG data.
Neal H. Clinthorne, University of Michigan (USA)
Chor-yi Ng, University of Michigan (USA)
W. Leslie Rogers, University of Michigan (USA)
It is often assumed that the photon arrival process incident on the photodetector array in a scintillation camera is Poisson, conditioned on the location and energy of each incident gamma-ray. A simple experiment, in which the covariance between the sensor outputs is empirically determined demonstrates that the observations are not independent conditioned merely on location and energy. We assume that this lack of independence arises from random parameters influencing the Poisson intensity or photodetector responses. Because, these responses can be difficult to either model or measure as a function of the nuisance parameters, we develop two simple approximations to the ideal maximum likelihood estimator for location and energy. These approximations have the advantage that they do not require complete knowledge of the response functions, and furthermore, their performance is comparable to that of the ideal estimator.
D. Kraus, Atlas Elektronik (GERMANY)
A. Beckmann, Atlas Elektronik (GERMANY)
A. Krupp, Atlas Elektronik (GERMANY)
S. Ries, Atlas Elektronik (GERMANY)
In this paper, we address the problem of estimating the components of superimposed expotentially decaying signals. Usual estimation techniques, e.g. least squares or eigenvalue and eigenvector based methods, are not adequate for exponentionally decaying fluorescence processes due to their rather simple signal modelling. Therefore, we introduce a better suited parametic model by exploiting the statistical properties of the exponentially decaying emission of fluorescence photons (time dependent Poisson statistics). Using this model maximum likelihood estimates for the fluorescence intensity spectrum and the decay parameters are derived. The performance of the maximum likelihood estimates is compared with the least squares estimates by means of simulations and real data experiments. The results indicate the superiority of the maximum likelihood estimates.
Mahmood R. Azimi-Sadjadi, Colorado State University
JoEllen Wilbur, Coastal Systems Station (USA)
Gerald J. Dobeck, Coastal Systems Station (USA)
A new approach for identifying the presence of resonance in the acoustic backscatter from unknown elastic targets by isolating the resonance part from the specular contribution is developed. The method allows for characterization of both the time history and time-scale of the resonant contribution of the target directly from the acoustic backscatter. An adaptive transversal filter structure is used to estimate the specular part of the backscatter and consequently the error signal would provide an estimate of the resonance part. This scheme does not require any underlying model assumption about the elastic return and further can be applied to targets of unknown geometry and thickness. The adaptation rule is based upon fast Recursive Least Squares (RLS) learning. Test results on acoustic data are presented which indicate the effectiveness of the proposed approach.
Zhiping Lin, Defence Science Organization (SINGAPORE)
Experimental results on the study of helicopter acoustic signals with nonstationary additive noises using cyclostationarity are presented. It is shown that helicopter signals are closely related to first-order periodicity rather than to second- or higher order periodicity, and hence it is necessary to discuss the feasibility of detecting first-order periodicity using cyclostationarity. Working on real helicopter data, we then show that some advantages of using cyclostationarity for helicopter signal detection are improvement of (cyclic) frequency resolution and enhancement of the probability of detection. For helicopter signals with time-variant Doppler shift, a cyclic frequency smoothing method is proposed. This method does not have a counterpart in communication applications, and should be useful for acoustic signal processing.
A. R. Leyman, University of Strathclyde (UK)
T.S. Durrani, University of Strathclyde (UK)
Eigendecomposition based techniques such as MUSIC and its variants constitute effective methods for determining the direction of arrival (DOA) estimates of narrowband sources. In this paper, a new strategy which extends the MUSIC algorithm to higher order statistics (HOS) is proposed for estimation of the DOA. Also, we present a new method for the estimation of the number of multiple narrowband incoherent and coherent non-Gaussian source signals arriving on the array which we consider as a significant contribution. The performance of the technique is compared with other recently suggested HOS-based methods.