Wavelet-based Data Reduction Techniques For Process Fault Detection.pdf

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Preview of Wavelet-based data reduction techniques for process fault detection
🔗 Source: sites.gatech.edu
📊 Size: 634 KB
👤 Author: Myong K. Jeong ; Jye-Chyi Lu ; Xiaoming Huo ; Brani Vidakovic ; Di Chen
⬇️ Downloads: 85

Summary

This article presents new data reduction methods based on the discrete wavelet transform to handle large and complicated nonstationary data curves, minimizing objective functions to balance data reduction and modeling accuracy, and evaluates their competitiveness with existing engineering data compression and statistical data denoising methods.

Description

This article presents new data reduction methods based on the discrete wavelet transform to handle large and complicated nonstationary data curves, minimizing...

Technical Information

  • File Format: PDF
  • File Size: 634 KB
  • Pages: 15
  • Language: EN
  • Author: Myong K. Jeong ; Jye-Chyi Lu ; Xiaoming Huo ; Brani Vidakovic ; Di Chen
  • Total Downloads: 85
  • Last Updated: 1 day ago

Document Overview

This PDF document about Wavelet-based data reduction techniques for process fault detection provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Wavelet-based data reduction techniques for process fault detection.

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