Probability Distribution Classification Processor
Abstract
This patent application discloses a system and method that preferably comprises several groups of artificial neural networks (ANNs) for classifying the probability distribution of random data. Each group of artificial neural networks is preferably trained to produce a selected output in response to data having a particular probability distribution, and each group preferably analyzes a different sample size of data. A parameter estimator module calculates statistical parameters for the different size data samples. The outputs of the several groups of artificial networks and of the parameter estimator are analyzed by a rule-based decision logic module which then selects the type of probability distribution that best describes the random data based on rules that correspond to ranges of values of the outputs of the artificial neural networks. (6 figures)
Document Details
- Document Type
- Technical Report
- Publication Date
- May 26, 2004
- Accession Number
- ADD020156
Entities
People
- Christopher M. Deangelis
Organizations
- United States Department of the Navy