A novel Prior-Weighted Sparse Optimization method for global sensor array selection in electronic noses

Zhifang Liang

doi:10.1016/j.snb.2026.140226

A novel Prior-Weighted Sparse Optimization method for global sensor array selection in electronic noses

2026-05-27

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DOI：10.1016/j.snb.2026.140226

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• Global sparse optimization efficiently optimizes e-nose sensor arrays. • Prior weights handle multicollinearity and suppress redundant sensors. • Fused metric integrates prior and posterior clues for robust evaluation. • Minimal sensor subsets achieve superior classification performance. • Experiments on diverse datasets validate the proposed method’s efficacy.

Keywords:

sparse optimization

sensor array selection

electronic noses

prior weights

fused metric

A novel Prior-Weighted Sparse Optimization method for global sensor array selection in electronic noses

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