Ian Barrodale

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Submittal of an algorithm for consideration for publication in Communicat ions of the A C M implies unrestricted use of the algorithm within a computer is permissible. Copyright @ 1974, Association for Computing Machinery, Inc. General permission to republish, but not for profit, all or part of this material is granted provided that ACM's copyright notice(More)
subject to the given constraints (2) and (3). (In expression (4), b, denotes the ith component of b and A, denotes the ith row of A.) The method is completely general in the sense that no restrictions are imposed on the ranks of the matrices A, C, and E, or on the signs of the elements of f. Furthermore, if no vector x satisfying (2) and (3) exists, the(More)
The development of reliable software tools to aid human interpretation of complex digital images is of increasing importance. In particular, change detection requires that two or more images be carefully overlaid (registered) using digital techniques that compensate for picture distortions caused by sensor motion, ambient conditions, etc. We are primarily(More)
This paper describes an algorithm for computing best l\, k and /(D approximations to discrete data, by functions of several parameters which depend nonlinearly on just one of these parameters. Such functions (e.g. «i + a2ef , a\ + a2 sin ex, (ai + a2x)l(l + ex)) often occur in practice, and a numerical study confirms that it is feasible to compute best(More)
A formulation of the maximum entropy (ME) method is described, where the data constraints are expressed in the form of fixed bounds on the elements of an orthogonal transform of the model. The bounds are set on the basis of both the observed data and an estimate of the noise statistics in the transform domain; prior knowledge, if available, can also be(More)
Received 3 June 1974 and 28 January 1975. Copyright (~) 1975, Association for Computing Machinery, Inc. General permission to republish, but not for profit, all or part of this material is granted provided that ACM's copyright notice is given and that reference is made to the publication, to its date of issue, and to the fact that reprinting privileges were(More)
When analyzing linear systems of equations, the most important indicator of potential instability is the condition number of the matrix. For a convolution matrix W formed from a series w (where Wij wi-, + ,, 1 5 i j + 1 5 k , W,j = 0 otherwise), this condition number defines the stabirity of the deconvolution process. For the larger convolution matrices(More)