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A globally convergent algorithm is presented for the solution of a wide class of semi-infinite programming problems. The method is based on the solution of a sequence of equality constrained quadratic programming problems, and usually has a second order convergence rate. Numerical results illustrating the effectiveness of the method are given.

1 Introduction 2 Existence theorems for the LSIS 3 Geometry of the feasible set 4 Optimality 5 Duality theorems and discretizatiön 6 Stability of the LSIS 7 Stability and well-posedness of the LSIP problem 8 Optimal Solution unicity REFERENCES 3 3 5 6 10 12 14 19 23 25

In many applications involving image reconstruction, signal observation time is limited. This emphasizes the requirement for optimal observation selection algorithms. A selection criterion using the trace of a matrix forms the basis of two existing algorithms, the Sequential Backward Selection and Sequential Forward Selection algorithms. Neither is optimal… (More)

Problems in signal processing and medical imaging often lead to calculating sparse solutions to under-determined linear systems. Methodologies for solving this problem are presented as background to the method used in this work where the problem is reformulated as an unconstrained convex optimization problem. The least squares approach is modified by an l… (More)

- Peter Renaud, Roy Kerr, Brian Woods, Bob Long, David Wiltshire, Ian Coope +6 others
- 2013

On 15 May, the Physics and Mathematics departments co-hosted a function at the staff club to celebrate Roy Kerr's Einstein Medal, to be awarded on 28 May at the University of Bern, and to farewell him prior to his move to Tauranga. CONGRATULATIONS Congratulations to Dr Liene Daukste on the successful defence of her PhD. Congratulations to Jenny Harlow and… (More)

Previous work has investigated the feasibility of using Eigenimage-based enhancement tools to highlight abnormalities on chest X-rays (Butler et al in J Med Imaging Radiat Oncol 52:244–253, 2008). While promising, this approach has been limited by computational restrictions of standard clinical workstations, and uncertainty regarding what constitutes an… (More)

- Rachael Tappenden, Ian Coope, Jennifer Brown, Shannon Ezzat, Anna MacDonald, Michael Snook +5 others
- 2010

RETIREMENT Associate Professor Ian Coope, who has been a valued member of the department for 31 years, will be retiring on 7 May 2010. He will, however, maintain an association with the department after this date. A formal retirement function will take place in May or June, but I want to take this opportunity to thank Ian for his contribution over the years… (More)

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