Peter Kootsookos | The University of Queensland, Australia (original) (raw)

Papers by Peter Kootsookos

… , 2005. ITCC 2005. …, 2005

Frank Adelstein Dharma P. Agrawal Igor Aizenberg Giovanni Aloisio Kazumaro Aoki Hamid Arabnia Vij... more Frank Adelstein Dharma P. Agrawal Igor Aizenberg Giovanni Aloisio Kazumaro Aoki Hamid Arabnia Vijayan Asari Michail Attalah Robert L. Baber Pascal Bamford Nick Barnes Emad Bataineh Lejla Batina Siddika Berna Ors Guido Bertoni Euro Blasi Rainer Bluemel Luca Breveglieri Constantine Butakoff Greg Byrd Massimo Cafaro Miriam Capretz Gabriele Carteni Jordi Castella-Roca Herwin Chan Pei-Min Chen Alex Chen Chia-Chu Chiang Jagadish Chintala Edward Christensen Chi-Kit Ronald Chung Vaughan Clarkson Pedro Henrique G. Coelho Nedeljko Cvejic ...

This paper extends earlier results by Ward, Kennedy and Williamson [1, for the design of broadban... more This paper extends earlier results by Ward, Kennedy and Williamson [1, for the design of broadband arrays with frequency-invariant (FI) beam patterns to the case where it is desired to place an exact null in a given direction. The beamforming is done using appropriately selected FIR filters. First, the previous results for generating FI beam patterns using FIR filters are briefly summarised. Second, new results which give the conditions required for exact nulls in the beam pattern for all frequencies in any, possibly non-FI, beam pattern are given. Third, a method of generating beam patterns which possess an exact null and which are close, in an L 2 sense, to an arbitrary FI pattern is presented. Finally, some preliminary experimental results which corroborate the theoretical findings are presented.

This paper examines the well-known problem of line detection, but where the lines are wider than ... more This paper examines the well-known problem of line detection, but where the lines are wider than one pixel. The motivation behind the paper is the extraction of road information from high resolution photogrammetry and Light Detection and Ranging (LIDAR) data. Wide lines cause varying problems during detection. The HOUGH or RADON transform approaches do not find the road centrelines accurately; diagonals of the thick lines are found instead whilst other methods also tend to be error prone. Our approach convolves a raw, pixelated, binary road classification with a complex-valued disk. The technique provides three separate pieces of information about the road or thick line: the centreline, the direction and the width of the road at any point along the centreline. The road centreline can be detected from the position of the peak of the magnitude image resulting from the complex convolution. Road width can also be estimated from the magnitude peak whilst the direction of the road may be obtained from the phase image.

That is, the model represents the training sequence well, but fails to generalise. In this paper,... more That is, the model represents the training sequence well, but fails to generalise. In this paper, we present a possible solution to this problem, which is to maximise a linear combination of the likelihood of the training data, and the entropy of the model. We derive the necessary equations for gradient based maximisation of this combined term. The performance of the system is then evaluated in comparison with three other algorithms, on a classification task using synthetic data. The results indicate that the method is potentially useful. The main problem with the method is the computational intractability of the entropy calculation.

| In this paper a hidden Markov model (HMM) technique for the estimation of the shape of a towed ... more | In this paper a hidden Markov model (HMM) technique for the estimation of the shape of a towed array is presented. It is assumed that there is a far eld source radiating sound containing possibly weak spectral lines. The technique uses either the Fourier coe cients at a given frequency computed from a single time block or the maximal eigenvector of a sample spectral covariance matrix. The technique is illustrated using simulations and real data. The results of the simulations indicate that the HMM technique yields shape and bearing estimates more accurate than those provided by a maximum likelihood array shape estimation technique.

Faulty rolling element bearings under very low shaft speed and light load exhibit vibrations whic... more Faulty rolling element bearings under very low shaft speed and light load exhibit vibrations which possess periodic envelope-autocorrelations.

In this paper, a general model of the signal from faulty rolling element bearings under the condi... more In this paper, a general model of the signal from faulty rolling element bearings under the condition of a heavy load is given. The envelope-autocorrelation of this proposed model in the case of very low shaft speed is given with a mathematical description. The simulated signals of rolling element bearings under the condition of a heavy load with inner race fault, outer race fault, and roller fault are generated using the model. In the power spectrum of signals, the characteristic frequency and its harmonics are submerged in the white noise, but they are obvious in the envelope-autocorrelation and envelopeautocorrelation power spectrum. It is demonstrated that the envelope-autocorrelation and its power spectrum are effective as to a fault detection technique.

In various communications-based adaptive array applications, the directions of arrival (DOAs) of ... more In various communications-based adaptive array applications, the directions of arrival (DOAs) of the desired user signal are sparsely separated. As such, the desired beam-pattern has a sparse structure. We propose an NLMS based adaptive algorithm which exploits this sparse DOA structure and provides significantly improved convergence speeds.

2005 13th European Signal Processing Conference, 2005

Dicta, 2003

An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the probl... more An algebraic curve is defined as the zero set of a multivariate polynomial. We consider the problem of fitting an algebraic curve to a set of vectors given an additional set of vectors labelled as interior or exterior to the curve. The problem of fitting a linear curve in this way is shown to lend itself to a support vector representation, allowing non-linear curves and high dimensional surfaces to be estimated using kernel functions. The approach is attractive due to the stability of solutions obtained, the range of functional forms made possible (including polynomials), and the potential for applying well understood regularisation operators from the theory of Support Vector Machines.

IEEE International Symposium on Circuits and Systems, 2000

T h i s paper describes a procedure for the time-frequency analysis of signals, based on Time-Fre... more T h i s paper describes a procedure for the time-frequency analysis of signals, based on Time-Frequency Distributions ("FDS) and Instantaneous Prequeney (IF) estimation. First, w e use a suitable TFD to deter-the number of signal components. Then, if the signal is monocomponent, the IF law can be estimated directly. For multicomponent signals, two-dimensional wiDdowing in the timefrequency (t-f) domain (a form of tirc-trprying filtering) is used to isolate each component: IP estimation i s then applied to the individual components. The periodic first moment of a TFD is used to estimate the IF. A suitable definition of the periodic first moment is proposed, and the relationship of these estimators to others based on the central finite difference of the phase of the analytic signal is given. A TBD such a8 the Wigner-Ville Distribution may be used to represent both IF and arplitude variations in the individual signal components at each stage of the analysis. 0. MTRODUCTION The representation of time-varying signals is a major problem in many signal processing applications. The Short time Fourier Transform (STFT) is often used in such cases. Model based approaches such as time-varying ARMA models have also been used. Time-frequency Distributions (TFIkr) haVC been introduced in an attempt to provide a general solution to this problem and can be considered as an extension to classical Fourier analysis. The latter is primarily designed to deal with stationary or quasi-stationary signals, while TFDS deal with non-stationary ones. Although the STFT is a general member of Cohenls class of Time-Frequency Eistributions (TFDs), B, partial integration over a sufficiently large region of the time-frequency (t-f) plane will not give the signal local energy contribution. W e say that TFDa such as the Wigner-Ville, Born-Jordan-Cohen and Choi-Williams which possess this property belong to the sub-class, cP' . A concept central to the selection of TFDs for practical analysis is that of instantaneous frequency (IF). The IF is a parameter which corresponds to the frequency of a sine w a n which locally matches the signal under analysis. Physically, it m a k e s sense only for monocomponent signals, i.e. where there is only one frequency or a narrow range of frequencies varying as a function of time [I]. For multicomponent sig-ISCAS '89 1237 nals, the notion of a single valued IF becomes meaningless -(see [ 2 ] for a good discussion on multicomponent signals). It is clear from the above that the nrst step of any general time-frequency analysis procedure is to determine whether the signal under analysis is monocomponent or multicomponent, and whether the signal is stationary or non-stationary. The analysis tool (chosen from Cohen's class of TFDs [ 2 ] ) must therefore possess the following three properties: P,: The tool dfscriminates between stationary and non-stationary signals. P,: The tool discriminates between monocomponent and multicomponent signals. PI: The tool allows a break-up of the multicomponent signal into its components (also timew i n q ) .

This paper develops an adaptive c o n troller for active vibration control. The method is based o... more This paper develops an adaptive c o n troller for active vibration control. The method is based on the LQG approach via disturbance modelling given in De Nicolao 1]. This approach to the narrow band disturbance rejection problem is then applied to the problem of eliminating the e ects of roll eccentricity in steel-strip rolling mills

2004 IEEE Region 10 Conference TENCON 2004., 2004

When developing a video gesture recognition system to recognise letters of the alphabet based on ... more When developing a video gesture recognition system to recognise letters of the alphabet based on hidden Markov Model (HMM) pattern recognition, we observed that by carefully selecting the model structure we could obtain greatly improved recognition performance. This led us to the questions: Why do some HMMs work so well for pattern recognition? Which factors affect the HMM training process? In an attempt to answer these fundamental questions of learning, we used simple triangle and square video gestures where good HMM structure can be deduced analytically from knowledge of the physical process. We then compared these analytic models to models estimated from Baum-Welch training on the video gestures. This paper shows that with appropriate constraints on model structure, Baum-Welch reestimation leads to good HMMs which are very similar to those obtained analytically. These results corroborate earlier work where we show that the LR banded HMM structure is remarkably effective in recognising video gestures when compared to fully-connected (ergodic) or LR HMM structures.