糖心vlog官网

• Biography/ Background

  Lang White obtained the degrees of B.Sc., B.E. (hons) and Ph.D. (Electrical Engineering) from the University of Queensland, Brisbane Australia in 1984, 1985 and 1989 respectively. From 1986-1999 he worked as a Research Scientist at the Defence Science and Technology Organisation Australia in the areas of radar and communications electronic warfare. Since 1999 he has been Professor in the School of Electrical and Electronic Engineering at the University of 糖心vlog官网. From 2002-2006, he was a Fellow with National ICT Australia Ltd.

  Attention - potential resesarch students (Ph D or M Phil) are being sought for 2020. If you are a domestic or international student in receipt of a scholarship, please contact Prof White directly.

  Please note that for national security reasons I am unable to accept foreign nationals as research students except for CAN/UK/US/NZ or NATO partner nationals.

  Other foreign nationals should direct enquiries to the graduate centre to seek alternative supervisors.

   

   

   

• Research Interests

  Professor White's research interests and activities lie in the general areas of statistical signal processing and control. Current projects include :

  1. Statistical modelling and estimation for hidden reciprocal chains (HRCs)

  HRCs are non-causal generalisations of hidden Markov chains and are one-dimensiona Markov random fields, although reciprocal processes are not, in general, Markovian. In this research, we investigate modelling, optimal state estimation, parameter estimation and model classification for HRCs. Applications addressed include "destination-aware" target tracking and the forensic analysis of "pattern-of-life" problems. Collaborators : Dr Francesco Carravetta (IASI-CNR, Italy) and Prof Vikram Krishnamurthy (UBC, Canada).

   

  2. Signal subspace methods for sensor array processing of temporally correlated signals

  This research is motivated by the question of whether temporal correlation in signals incident of a sensor array can be used to improve source localisation and classification. Advances in computational power mean that previously neglected techniques such as maximum likelihood estimation now become feasible. Recent results concerning the asymptotic consistency of certain estimators (Generalised Statistical Analysis) has also raised the question of whether these approaches can be used in signal subspace based methods such as ESPRIT. This project investigates a range of questions related to these two problems. Collaborators : Prof Peter Sherman (Iowa State Univ., USA), Defence Science and Technology Organisation Australia.

   

  3. Markov Decision Processes and State Aggregation

  This work is concerned with the development of sub-optimal control strategies for very large Markov decision processes, where state aggregation is used to reduce dimensionality. Models considered include Quasi Birth-Death processes and optimally lumped processes.

   

   

  4. Signal processing for GPS interference mitigation

  Funded by an ARC Linkage grant, and building on previous work cinducted in the School, this work is concerned with localisation and mitigation of jammers/spoofers in the GPS bands. Much critical infrastructure (e.g. aviation, ports, mining) relies on GPS localisation and the issue of dealing with deliberate or unintentional interference is very important. This project teams with the University of NSW and GPSat Systems.

   

  5. Game theory and applications

  Game theory is the study of multiple agents competing for resources (payoff, profit, reward). I am interested in the development of theoretical frameworks and adaptive algorithms for finding equilibria in games. Of particular interest are satisfaction games and Stackelberg games. Applications include resource allocation in wireless communications, analysis of discourse and balanced allocations.

   

   

  Note for students interested in undertaking a Higher Degree by Research (HDR) under my Supervision

  Any potential students interested in undertaking an HDR (M Phil or Ph D) under my supervision should firstly apply for enrolment through the normal university procedures. You can find information at http://www.adelaide.edu.au/study/postgraduate/research-degrees/. International students should note that supervisors do not generally provide financial support for HDR students, and that University scholarship opportunities are very competitive. You are also encouraged to seek other avenues for financial support through government and non-government organisations in your country of citizenship/residence or through bilateral arrangements between Australia and other countries.

  International Students : Please do not send me proposals directly unless you already have a scholarship, or are funded from other sources.
  

  Please also note that there are some restrictions on the eligibility of students from certain countries. You should consult the International Students Office for details.

  For Australian nationals or permanant residents (domestic students), financial support in the form of fee-waivers and/or living allowances may be available. The minimum qualification required is an honours degree or equivalent, although not everyone eligible for enrolment is guaranteed financial support. You should check with the 糖心vlog官网 Graduate Centre for details. Domestic students with First class honours, Masters degrees by research, or with a significant publication record may contact me in the first instance, providing a copy of your CV, a list of publications and an expression of the area of your research interests.

   

  Past and Current Graduate Students

  Dr Jianghe Zhou (completed)

  Dr Zhou's research examines the application of modern adaptive control theory and game theory to managing network traffic flow using window based methods such as TCP. Issues such as improved fairness in bandwidth allocation and the role of co-operation between users are addressed.

  Dr Gautam Balasubramanian (completed - winner of the Dean's Prize)

  Dr Balasubramanian's research is concerned with hyperspectral imaging. New methods are developed which assist a human analyst with the task of identifying and classifying anomalous materials in an hyperspectral image covering the visible to short-wave infra-red bands with a ground resolution of about 1 square metre. Recent advances in statistical modelling and processing of compositional models can result in improved detection accuracy with significant reduction in processing load. Mr Balasubramanian is supported by the Defence Science and Technology Organisation.

  Mr George Stamatescu (commenced Jul 2014)

  Mr Stamatescu's research interests are focussed on hiddern reciprocal processes and application in tracking in video imagery. Of main interest is parameter estimation (model learning) and linear approximations. Also studying fundamentals of machine learning algorithms such as binary neural networks.

  Mr Riley Bruce-Doust (M Phil - completed. Dean's commendation.)

  Mr Bruce-Doust's research interests are in the area of statistical modelling for target tracking with an emphasis on tracking moving objects in severe clutter with occlusions. Forgetting dynamics of reciprocal chains and related filters/smoothers also addressed.

  Dr Duong Nguyen (completed)
  

  Mr Nguyen's research focusses on signal processing challenges for emerging 5G wireless data systems, in particular the application of game theory to resource allocation. 

• Publications

  Many of my past publications are available on Research Gate at www.researchgate.net

   The following lists some recent highlights.

   2018

  L. Yu, F. Ma, E.-G. Lim, E. Cheng and L. B. White, ``Rational Orthogonal Wavelet-based Active Sonar Pulse and Detector Design'', IEEE Journal of Oceanic Engineering, accepted for publication, 12 Jan. 2018.

  D. D. Nguyen, H. X. Nguyen and L. B. White, ``Evaluating Performance of RAT Selection Algorithms for 5G HetNets'', IEEE Access, v. 6, no. 1, December 2018, pp. 61212-61222.

   

  2017

  L. B. White and F. Carravetta, ``Stochastic Realisation and Optimal Smoothing for Gaussian Generalised Reciprocal Processes'', Proc. IEEE Conference on Decision and Control, Melbourne, Dec. 2017, to appear.

  A. Borri, F. Carravetta and L. B. White, ``Smoothing of Spherical Markov Fields : Application to Climate Data Processing'', Proc. IEEE Conference on Decision and Control, Melbourne, Dec. 2017, to appear.

  L. B. White and F. Carravetta, ``Normalised Optimal Smoothers for a Class of Hidden Generalised Reciprocal Processes'', IEEE Trans. Automatic Control, published 17 Jan. 2017. DOI: 10.1109/TAC.2017.2654963

  D. D. Nguyen, H. X. Nguyen and L. B. White, ``Reinforcement Learning using Feedback for Heterogeneous RAT Selection'', IEEE Transactions on Wireless Communications, v. 16, no. 9, pp. 6062-6076, Sep. 2017 .

   

  G. Stamatescu, L. B. White and R. Bruce-Doust, ``Track Extraction for Hidden Reciprocal Chains'', IEEE Trans. Automatic Control, published 18 Aug 2017, DOI : 10.1109/TAC.2017.2741919.

   

  2016

  A. Borri, F. Carravetta and L. B. White, "Optimal Smoothing for Spherical Gauss-Markov Random Fields with Application to Weather Data Estimation", European Journal of Control, 2016.

  D. D. Nguyen, L. B. White and H. X. Nguyen, "Adaptive Multi-agent Reinforcement Learning with Non-positive Regret", Proc. 29th Australasian Joint Conf. Artificial Intelligence, Hobart, Dec. 2016.

  D. D. Nguyen, H. X. Nguyen and L. B. White, "Performance of Adaptive RAT Selection Algorithms in 5G Heterogeneous Wireless Networks", Proc. IEEE Int. Conf. Telecommunications Networks and Applications, New Zealand, Dec. 2016.

  2015

  Y. Guo and L. B. White, "Plane Sweep Method for Optimal Line Fitting in Track-before-detect", Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, Brisbane, 2015.

  G. Stamatescu, A. Dick and L. B. White, "Multi-camera Tracking of Intelligent Targets with Hidden Reciprocal Chains", Proc. Int. Conf. on Digital Image Computing : Techniques and Applications, 糖心vlog官网, 2015.

  2014

  Y. Yassir and L. B. White, "Folding Algorithm for Policy Evaluation for Markov Decision Processes with Quasi-Birth Death Structure", IEEE Transactions on Automatic Control, accepted for publication 13 Jan 2014.

  L. B. White and P. J. Sherman, "ML Estimation and CRB for Narrowband AR Signals on a Sensor Array", accepted for IEEE Int. Conf. on Acoustics, Speech and Signal Processing, Firenze, Italia, May 2014.

  L. B. White and F. Carravetta, "New Normalised Bayesian Smoothers for for Signals Modelled by Non-causal Compositions of Reciprocal Chains", Proc. IEEE Statistical Signal Processing Workshop, Gold Coast, 2014.

  2013

  A. C. Zecchin, M. F. Lambert, A. R. Simpson and L. B. White, "Parameter Identication in Pipeline Networks : A Transient Based Expectation-Maximisation Approach for Systems Containing Unknown Boundary Conditions", J. Hydraulic Engineering, accepted for publication 19 Nov. 2013.

  L. B. White and H. X. Vu, "Maximum likelihood sequence estimation for hidden reciprocal processes", IEEE Transactions on Automatic Control, v. 58, no. 10, 2013, pp. 2670-2674.

  A. C. Zecchin, L. B. White, M. F. Lambert and A. R. Simpson, "Parameter Identification of Fluid Line Networks by Frequency Domain Maximum Likelihood Estimation", Mechanical Systems and Signal Processing, v. 37, no. 1-2, 2013, pp. 370-387.

  2012

  F. Carravetta and L. B. White, "Modelling and Estimation for Finite State Reciprocal Processes", IEEE Transactions on Automatic Control, v.57, no. 9, 2012, pp. 2190-2202.

  2011

  L. B. White and F. Carravetta, "Optimal Smoothing for Hidden Reciprocal processes", IEEE Transactions on Automatic Control, v. 56, no. 9, 2011, pp. 2156-2161.

  2010

  A. C. Zecchin, M. F. Lambert, L. B. White and A. R. Simpson, "Modelling Transient Behaviour of a Pipe Network comprised of Lumped and Distributed Components by a Laplace-domain Admittance Matrix", Journal of Hydraulic Engineering, v. 136, no. 10, 2010, pp. 739-755.

Entry last updated: Thursday, 15 Dec 2022

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