Nonlinear model reduction by deep autoencoder of noise response data

DOI 機関リポジトリ (HANDLE) PDF 被引用文献1件 オープンアクセス

説明

In this paper a novel model order reduction method for nonlinear systems is proposed. Differently from existing ones, the proposed method provides a suitable non-linear projection, which we refer to as control-oriented deep autoencoder (CoDA), in an easily implementable manner. This is done by combining noise response data based model reduction, whose control theoretic optimality was recently proven by the author, with stacked autoencoder design via deep learning.

収録刊行物

被引用文献 (1)*注記

もっと見る

関連プロジェクト

もっと見る

詳細情報 詳細情報について

問題の指摘

ページトップへ