✨
AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
We also present a regularization of the local times and show a convergence result in Hida distributions space.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:We study an existence result in the mean square sense of the local times of a one-dimensional Gaussian process defined by an indefinite Wiener integral.
📊
Key Findings & Data:For any spatial dimension, we prove that the local times of a Gaussian process, after appropriatelly renormalized, exist as White noise distributions.
💡
Conclusion & Impact:We also present a regularization of the local times and show a convergence result in Hida distributions space.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Local times · b-Gaussian process · white noise analysis.
Abstract
We study an existence result in the mean square sense of the local times of a one-dimensional Gaussian process defined by an indefinite Wiener integral. For any spatial dimension, we prove that the local times of a Gaussian process, after appropriatelly renormalized, exist as White noise distributions. We also present a regularization of the local times and show a convergence result in Hida distributions space.
🔖
Cite This Article
Suryawan, H. P. (2018). Existence and regularization of the local times of a Gaussian process. Hacettepe Journal of Mathematics and Statistics, Volume: 47 Issue: 5. https://ajindex.com/articles/1402889