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In this paper, we propose a low decay, low bias dataset synthesis framework that models Machine Learning (ML) dataset theory using Python classes and ...
Sep 9, 2019 · Abstract—In this paper, we propose a low decay, low bias. dataset synthesis framework that models Machine Learning (ML) ; I. · Radio Frequency (RF) ...
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Jan 26, 2022 · Here we demonstrate a universal framework using backpropagation to directly train arbitrary physical systems to execute DNNs, that is, PNNs. Our ...
A neural network could be trained to infer the chan- nel directly based on the I/Q samples, without requiring additional pilots. One possible strategy could be ...
Apr 23, 2019 · We vision that the appealing deep learning-based wireless physical layer frameworks will bring a new direction in communication theories and ...
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Dec 9, 2023 · This paper presents a comprehensive investigation of GAI's applications for communications at the physical layer, ranging from traditional issues, including ...
Aug 7, 2024 · Here we develop a method called fully forward mode (FFM) learning, which implements the compute-intensive training process on the physical system.
In machine learning, a neural network is a model inspired by the structure and function of biological neural networks in animal brains. An artificial neural ...
Wireless communication technologies have experienced an extensive development to satisfy the applications and services in the wireless network.
Feb 28, 2019 · ABSTRACT. Modern radios, such as 5G New Radio, feature a large set of physical- layer control knobs in order to support an increasing number ...
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