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Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
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Inverting Monotonic Nonlinearities by Entropy Maximization.

Jordi Solé-Casals1, Karmele López-de-Ipiña Pena2, Cesar F Caiafa3

  • 1Data and Signal Processing Research Group, U Science Tech, University of Vic - Central University of Catalonia, Vic, Catalonia, Spain.

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Summary
This summary is machine-generated.

This study introduces the MaxEnt algorithm for blind inversion of monotonic nonlinear maps, improving source separation and Wiener system inversion. MaxEnt effectively compensates nonlinear distortions, outperforming existing methods in signal-to-noise ratio.

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Area of Science:

  • Signal Processing
  • Machine Learning
  • Information Theory

Background:

  • Blind inversion of nonlinear maps is crucial for source separation and Wiener system inversion.
  • Existing methods struggle with accurately estimating nonlinear components in mixed random variables.

Purpose of the Study:

  • Propose a novel blind inversion method for monotonic nonlinear maps.
  • Decouple nonlinear compensation from linear estimation for improved accuracy.
  • Introduce the MaxEnt algorithm as a generalized Gaussianization approach.

Main Methods:

  • Developed the MaxEnt algorithm, generalizing Gaussianization by maximizing entropy.
  • Implemented two versions: polynomial and neural network parameterizations.
  • Established sufficient conditions for successful nonlinear compensation.

Main Results:

  • MaxEnt successfully compensates monotonic nonlinear distortions.
  • Outperforms existing algorithms in Signal to Noise Ratio (SNR), especially with fewer variables.
  • Demonstrates robustness with minimal result variability.

Conclusions:

  • The MaxEnt algorithm offers a powerful and robust solution for blind nonlinear map inversion.
  • Its ability to decouple nonlinear and linear estimation simplifies complex signal processing tasks.
  • MaxEnt provides a significant advancement in source separation and system inversion.