Nonnegative Signal Decomposition with Supervision

Teng Li, Huan Chang and Jun Wu

Mathematical Problems in Engineering, 2013, vol. 2013, 1-8

Abstract:

This paper presents a novel algorithm to numerically decompose mixed signals in a collaborative way, given supervision of the labels that each signal contains. The decomposition is formulated as an optimization problem incorporating nonnegative constraint. A nonnegative data factorization solution is presented to yield the decomposed results. It is shown that the optimization is efficient and decreases the objective function monotonically. Such a decomposition algorithm can be applied on multilabel training samples for pattern classification. The real-data experimental results show that the proposed algorithm can significantly facilitate the multilabel image classification performance with weak supervision.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:620537

DOI: 10.1155/2013/620537

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