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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Self-normalised Distance with Don’t Cares
verfasst von : Peter Clifford, Raphaël Clifford
Erschienen in: Combinatorial Pattern Matching
Verlag: Springer Berlin Heidelberg
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We present
O
(
n
log
m
) algorithms for a new class of problems termed
self-normalised distance with don’t cares
. The input is a pattern
p
of length
m
and text
t
of length
n
>
m
. The elements of these strings are either integers or wild card symbols. In the shift version, the problem is to compute
$\min_{\alpha}\sum_{j=0}^{m-1}(\alpha + p_j - t_{i+j})^2$
for all
i
, where wild cards do not contribute to the sum. In the shift-scale version, the objective is to compute
$\min_{\alpha,\beta}\sum_{j=0}^{m-1}(\alpha+ \beta p_j - t_{i+j})^2$
for all
i
, similarly. We show that the algorithms have the additional benefit of providing simple
O
(
n
log
m
) solutions for the problems of exact matching with don’t cares, exact shift matching with don’t cares and exact shift-scale matching with don’t cares.