Discriminative dimensionality reduction for sensor drift compensation in electronic nose: A robust, low-rank, and sparse representation method

标题
Discriminative dimensionality reduction for sensor drift compensation in electronic nose: A robust, low-rank, and sparse representation method
作者
关键词
Sensor drift, electronic nose, Dimensionality reduction, Domain adaptation, Transfer learning, Low-rank and sparse representation
出版物
EXPERT SYSTEMS WITH APPLICATIONS
Volume 148, Issue -, Pages 113238
出版商
Elsevier BV
发表日期
2020-01-24
DOI
10.1016/j.eswa.2020.113238

向作者/读者发起求助以获取更多资源

Reprint

联系作者

Find the ideal target journal for your manuscript

Explore over 38,000 international journals covering a vast array of academic fields.

Search

Create your own webinar

Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.

Create Now