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首页> 外文期刊>IFAC PapersOnLine >Extension of First-Order Stable Spline Kernel to Encode Relative Degree * * This work is supported by Grant-in-Aid for JSPS Research Fellow grant number JP15J05700, JSPS KAKENHI grant number JP16H06093, and JSPS KAKENHI grant number JP16K14284
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Extension of First-Order Stable Spline Kernel to Encode Relative Degree * * This work is supported by Grant-in-Aid for JSPS Research Fellow grant number JP15J05700, JSPS KAKENHI grant number JP16H06093, and JSPS KAKENHI grant number JP16K14284

机译：扩展一阶稳定样条内核以对相对度进行编码 * < ce：footnote id =“ fn1”> * Grant-in-Aid支持JSPS，这项工作研究员奖学金编号JP15J05700，JSPS KAKENHI资助编号JP16H06093和JSPS KAKENHI资助编号JP16K14284

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摘要

This paper focuses on the kernel-based system identification methods, which estimate the impulse response of the target system in the Bayesian estimation framework. This paper discusses about continuous-time systems, and proposes a new kernel based on a prior that the relative degree of the target system is higher than or equal to two. Such a prior is identical to a prior on the continuity of the impulse response at time zero. The proposed kernel is an extension of the first-order Stable Spline kernel, which is one of the most famous kernels. Numerical examples are shown to demonstrate the effectiveness of the proposed kernel.
机译：本文重点研究基于核的系统识别方法，该方法在贝叶斯估计框架中估计目标系统的脉冲响应。本文讨论了连续时间系统，并基于目标系统相对程度大于或等于2的先验提出了一个新的内核。这样的先验与时间零时脉冲响应的连续性先验相同。提议的内核是一阶稳定样条线内核的扩展，后者是最著名的内核之一。数值例子表明了所提出的内核的有效性。

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