DPD 和 PA 建模
使用神经网络对功率放大器 (PA) 进行建模。为了抵消 PA 中的非线性效应，您可以使用神经网络对输入信号应用数字预失真 (DPD)。有关工作流的描述，请参阅AI for Digital Predistortion Design。
主题
- AI for Digital Predistortion Design
Example workflows for training, compressing, and using a deep learning network for digital predistortion design. (自 R2024a 起)
- Power Amplifier Modeling Using Neural Networks
Model a power amplifier (PA) using several different neural network (NN) architectures. (自 R2024a 起)
精选示例
Compare Residual Recurrent Neural Network Structures for Digital Predistortion Design
Compare residual RNN structures for a digital predistortion (DPD) design.
Data Preparation for Neural Network Digital Predistortion Design
Prepare data for training a neural network digital predistortion (DPD) system. The DPD is used to offset the effects of nonlinearities in a power amplifier (PA).
Neural Network for Digital Predistortion Design-Offline Training
Use a neural network, that is trained offline, to apply digital predistortion to offset the effects of nonlinearities in a power amplifier.
Neural Network for Digital Predistortion Design - Online Training
Use a neural network, that is trained online, to apply digital predistortion to offset the effects of nonlinearities in a power amplifier.
Structurally Compress Neural Network DPD Using Projection
Structurally compress a neural network DPD to reduce computational complexity and memory requirements using projection and principal component analysis.
Power Amplifier Modeling Using Neural Networks
Model a power amplifier (PA) using several different neural network (NN) architectures.
