Synergistic Effects of Phase Folding and Wavelet Denoising with Applications in Light Curve Analysis

Abstract

The growing size of cosmological data sets is causing the current human-centric approach to cosmology to become impractical. Autonomous data analysis techniques need to be developed in order to advance the field of cosmology. This research examines the benefits of combining two signal analysis techniques, namely phase folding and wavelet denoising, into a newly-developed suite of autonomous light curve analysis tools which includes aspects of component extraction and period detection. The improvements these tools provide, with respect to autonomy and signal quality, are demonstrated using both simulated and real-world light curve data. Although applied to light curve data, the suite of tools developed in this dissertation are advantageous to the processing, modeling, or extractions to any periodic signal analysis.

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Document Details

Document Type
Technical Report
Publication Date
Sep 15, 2016
Accession Number
AD1017864

Entities

People

  • Andrew Armstrong

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Big Data
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Databases
  • Department Of Defense
  • Governments
  • Information Science
  • Periodic Functions
  • Regression Analysis
  • Statistical Analysis
  • Statistical Distributions
  • Surveys
  • United States Government

Readers

  • Astronomy/Astrophysics
  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development