Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models

Min Gan,Yu Guan,Guang-Yong Chen,C L Philip Chen

IEEE Transactions on Neural Networks and Learning Systems（2021）

引用 33|浏览7

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摘要

In this article, we study the recursive algorithms for a class of separable nonlinear models (SNLMs) in which the parameters can be partitioned into a linear part and a nonlinear part. Such models are very common in machine learning, system identification, and signal processing. Utilizing the special structure of the SNLMs, we propose a recursive variable projection (RVP) algorithm, in which at ea...

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关键词

Signal processing algorithms,Adaptation models,Gallium nitride,Computer science,Machine learning algorithms,Numerical models,Convergence

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