An **Abstract Wiener space** is a mathematical framework used in the study of stochastic processes and has applications in probability theory and functional analysis. It is a generalization of the concept of a Wiener space (or Brownian motion space) and provides a rigorous foundation for the analysis of Gaussian measures on infinite-dimensional spaces. An Abstract Wiener space consists of three main components: 1. **Hilbert Space**: A separable Hilbert space \( H \) serves as the underlying space.
Articles by others on the same topic
There are currently no matching articles.