Intelligent analysis system for signal processing tasks based on LSTM recurrent neural network algorithm

03-09-2021
S.I.: Machine Learning based semantic representation and analytics for multimedia application

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Authors: Ya Zhou; Xiaobo Jiao
Published in: Neural Computing and Applications | Issue 15/2022

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Abstract

The article introduces an intelligent analysis system for signal processing tasks based on LSTM recurrent neural networks, focusing on the challenges of modulation recognition in complex communication environments. It highlights the development of a hybrid CNN-LSTM model to improve DOA estimation performance in low signal-to-noise ratio and high reverberation conditions. The system's performance is validated through extensive experiments, demonstrating its effectiveness in signal processing tasks. The article also provides a comprehensive review of related work in signal processing and deep learning, positioning its contribution within the broader context of advancements in the field.

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Title: Intelligent analysis system for signal processing tasks based on LSTM recurrent neural network algorithm
Authors: Ya Zhou
Xiaobo Jiao
Publication date: 03-09-2021
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 15/2022
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-021-06478-6

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Intelligent analysis system for signal processing tasks based on LSTM recurrent neural network algorithm

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