2023
DOI: 10.1016/j.prime.2023.100335
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Variational autoencoder-enhanced deep neural network-based detection for MIMO systems

Gevira Omondi,
Thomas O. Olwal
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Cited by 3 publications
(1 citation statement)
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“…However, scalability issues in handling complex state spaces with DQN require further research and refinement. Moreover, variational autoencoders (VAEs) contribute to a deeper understanding of data distribution for product design and quality control in manufacturing (Omondi & Olwal, 2023). Nonetheless, limitations persist in their handling of nonlinear trends and complex patterns, demanding additional research to enhance their applicability.…”
Section: Research On Deep Learning In the Digital Economy Manufacturi...mentioning
confidence: 99%
“…However, scalability issues in handling complex state spaces with DQN require further research and refinement. Moreover, variational autoencoders (VAEs) contribute to a deeper understanding of data distribution for product design and quality control in manufacturing (Omondi & Olwal, 2023). Nonetheless, limitations persist in their handling of nonlinear trends and complex patterns, demanding additional research to enhance their applicability.…”
Section: Research On Deep Learning In the Digital Economy Manufacturi...mentioning
confidence: 99%