A Hybrid LSTM-ResNet Deep Neural Network for Noise Reduction and Classification of V-Band Receiver Signals

A Hybrid LSTM-ResNet Deep Neural Network for Noise Reduction and Classification of V-Band Receiver Signals

Noise reduction is one of the most important process used for signal processing in communication systems. The signal-to-noise ratio (SNR) is a key parameter to consider for minimizing the bit error rate (BER). The inherent noise found in millimeter-wave systems is mainly a combination of white noise...

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Bibliographic Details
Main Authors: Homa Arab, Iman Ghaffari, Romaric Mvone Evina, Serioja Ovidiu Tatu, Steven Dufour
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
convolutional neural network (CNN)
deep learning
denoising
Doppler frequency
long short-term memory (LSTM)
Online Access:https://ieeexplore.ieee.org/document/9705207/

Internet

https://ieeexplore.ieee.org/document/9705207/

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