AES E-Library

Adaptive Predistortion Filter for Linearization of Digital PWM Power Amplifier using Neural Networks

The paper presents a method to compensate for nonlinear distortion of digital Pulse Width Modulation (PWM) power amplifiers by prefiltering the input signals using artificial neural networks. We first construct a model of the digital amplifier using artificial neural networks. Using this model, the artificial neural network model of a predistortion filter is trained such that the combined system, the digital amplifier and predistortion filter, produces an output, that is linearly proportional to the input. The simulation results show that the artificial neural networks of the predistortion filter can effectively correct the nonlinear distortion of the digital amplifier.

Authors: Yang, Minki; Oh, Jong-Hoon
Affiliations: PULSUS Technologies, Inc., Seoul, Korea ; Pohang University of Science and Technology, Pohang, Kyungbuk, Korea(See document for exact affiliation information.)
AES Convention:113 (October 2002) Paper Number:5657 Import into BibTeX
Subject:Signal Processing

Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.

Learn more about the AES E-Library

E-Library Location: (CD aes19)   /pp2002/pp0210/000192.pdf

Start a discussion about this paper!