We present a local density estimator based on first order statistics. To estimate the density at a point, x, the original sample is divided into subsets and the average minimum sample distance to x over all such subsets is used to define the density estimate at x. The tuning parameter is thus the number of subsets instead of the typical bandwidth of kernel or histogram-based density estimators....

with 3 edits (delete the C, delete the last A and insert a C). This is the best that can be done so the minimum edit distance is 3. The MED problem is an important problem that has many applications. For example in version control systems such as git or svn when you update a file and commit it, the system does not store the new version but instead only stores the “difference” from the previous ...

A new bound on the minimum distance of q-ary cyclic codes is proposed. It is based on the description by another cyclic code with small minimum distance. The connection to the BCH bound and the Hartmann–Tzeng (HT) bound is formulated explicitly. We show that for many cases our approach improves the HT bound. Furthermore, we refine our bound for several families of cyclic codes. We define syndro...