Sparse density estimator with tunable kernels
A new sparse kernel density estimator with tunable kernels is introduced within a forward constrained regression framework whereby the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Based on the minimum integrated square error criterion, a recursive algor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2016-01-15.
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| Subjects: | |
| Online Access: | Get fulltext |