A Theory of Generalized Random Processes and Its Applications,
Abstract
A class of generalized random processes is defined in the framework of vector-valued distributions (or vector-valued generalized functions). Namely, a generalized random process in this class is a continuous linear transformation from a topological vector space of measuring (test) functions to a Banach space of random variables. A theory of the generalized random processes is developed based on the well developed work on the generalized functions. The generalized random process is an extended notion of a generalized function, and all generalized functions belong to the class of generalized random processes. Two sequences of spaces of generalized random processes are defined on the Sobolev spaces of measuring functions in two different ways. The so-called white Gaussian process is characterized in the framework of generalized random processes. The theory of generalized random processes developed here is applied to the estimation problems which involve the white Gaussian process or white process.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 1972
- Accession Number
- AD0752644
Entities
People
- Hiroshi Inaba
Organizations
- University of Texas at Austin