Enhanced System for Detection of Randomness in Sparse Time Series Distributions

Abstract

A two-step method and apparatus are provided for automatically characterizing the spatial arrangement among the data points of a time series distribution in a data processing system wherein the classification of said time series distribution is required. In a first stage, the method and apparatus utilize a grid in Cartesian coordinates to determine (1) the number of cells in the grid containing at least one input data point of the time series distribution; (2) the expected number of cells which would contain at least one data point in a random distribution in said grid; and (3) an upper and lower probability of false alarm above and below said expected value utilizing a discrete binomial probability relationship in order to analyze the randomness characteristic of the input time series distribution. In a second stage, a statistical test of significance of the sparse data is utilized to determine the existence of noise and/or signal whereby a comparison of the results from the first stage and the second stage increase the probability of distinguishing noise from signal.

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Document Details

Document Type
Technical Report
Publication Date
Mar 03, 2004
Accession Number
ADD020144

Entities

People

  • Francis J. O'brien

Organizations

  • United States Department of the Navy

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Binomials
  • Cartesian Coordinates
  • Data Processing
  • Data Sets
  • Detection
  • False Alarms
  • Grids
  • Information Processing
  • Information Science
  • Mathematical Analysis
  • Operating Systems
  • Probability
  • Probability Distributions
  • Statistical Tests
  • Statistics
  • Undersea Warfare
  • Warning Systems

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Statistical inference.