کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6958043 | 1451936 | 2017 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Online kernel nonnegative matrix factorization
ترجمه فارسی عنوان
فاکتور سازی ماتریس غیرقطعی هسته آنلاین
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
Nonnegative matrix factorization (NMF) has become a prominent signal processing and data analysis technique. To address streaming data, online methods for NMF have been introduced recently, mainly restricted to the linear model. In this paper, we propose a framework for online nonlinear NMF, where the factorization is conducted in a kernel-induced feature space. By exploring recent advances in the stochastic gradient descent and the mini-batch strategies, the proposed algorithms have a controlled computational complexity. We derive several general update rules, in additive and multiplicative strategies, and detail the case of the Gaussian kernel. The performance of the proposed framework is validated on unmixing synthetic and real hyperspectral images, comparing to state-of-the-art techniques.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 131, February 2017, Pages 143-153
Journal: Signal Processing - Volume 131, February 2017, Pages 143-153
نویسندگان
Fei Zhu, Paul Honeine,