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Convention Paper

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

Authors: Yang, Minki; Oh, Jong-Hoon

AES Convention 113 · Paper 5657 · October 2002

Abstract

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.

Details

Published in
AES Convention 113
AES Convention
113
Paper number
5657
Publication date
October 6, 2002
Session subject
Signal Processing
Affiliation
PULSUS Technologies, Inc., Seoul, Korea ; Pohang University of Science and Technology, Pohang, Kyungbuk, Korea (See document for exact affiliation information.)
Type
Convention Paper