カーネルベースのシステム識別は,一般化された正交ベース関数とメタヒューリスティックテクニックを使用します
1Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150006, China.
ISA transactions
|August 26, 2025
まとめ
この研究は,システム識別におけるカーネルベースの正規化 (KRM) の新しい方法を提示します. 強化されたカーネル設計とメタヒューリスティックハイパーパラメータ最適化は,モデル推定性能を改善します.
科学分野:
- 制御システム工学
- 機械学習
- 信号処理
背景:
- カーネルベースの正規化方法 (KRM) は,因果的および非因果的システムの両方のシステム識別において重要なものです.
- KRMの主要な課題は,カーネルの設計とハイパーパラメータ推定です.
- 既存のKRMアプローチは これらの課題に対して 堅実な解決策を必要としています
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