作者：GRENANDER, U; MILLER, MI
作者单位：Brown University; Washington University (WUSTL)
摘要：Modern sensor technologies, especially in biomedicine, produce increasingly detailed and informative image ensembles, many extremely complex. It will be argued that-pattern theory can supply mathematical representations of subject-matter knowledge that can be used as a basis for algorithmic 'understanding' of such pictures. After a brief survey of the basic principles of pattern theory we shall illustrate them by an application to a concrete situation: high magnification (greater than 15000 x)...
作者：MARRON, JS; RUPPERT, D
作者单位：Cornell University; University of North Carolina; University of North Carolina Chapel Hill
摘要：We consider kernel estimation of a univariate density whose support is a compact interval. If the density is non-zero at either boundary, then the usual kernel estimator can be seriously biased. 'Reflection' at a boundary removes some bias, but unless the first derivative of the density is 0 at the boundary the estimator with reflection can still be much more severely biased at the boundary than in the interior. We propose to transform the data to a density that has its first derivative equal ...
