Results 11 to 20 of about 2,336,734 (289)
Adaptive procedure for automatic modulation recognition [PDF]
Journal of Telecommunications and Information Technology, 2004 An adaptive procedure for automatic modulation recognition is described. With it the automatic modulation classification and recognition of radio communication signals with a priori unknown parameters is possible effectively.
Ferdinand Liedtke
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Deep Learning Based Sub-Nyquist Modulation Recognition [PDF]
, 2023 In this paper, we designed a Convolutional Neural Network (CNN) for Sub-Nyquist modulation recognition and compare the performance Long Short-Term Memory (LSTM) network and Convolutional Long Short-term Deep Neural Network (CLDNN) respectively.
Li, S, Hu, S, Nilavalan, N
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On the benefits of robust models in modulation recognition [PDF]
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 2021 Given the rapid changes in telecommunication systems and their higher dependence on artificial intelligence, it is increasingly important to have models that can perform well under different, possibly adverse, conditions. Deep Neural Networks (DNNs) using convolutional layers are state-of-the-art in many tasks in communications.
Maroto Morales, Javier Alejandro +2 more
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Dynamic Equilibrium Module for Action Recognition [PDF]
IEEE Access, 2021 Temporal variations, such as sudden motion, acceleration and occlusions, occur frequently in real-world videos and force video-modeling networks to account for them. However. often they are not beneficial for recognizing actions at coarse granularity and thus may impede spatio-temporal learning.
Qili Zeng +2 more
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Deep architectures for modulation recognition [PDF]
2017 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2017 We survey the latest advances in machine learning with deep neural networks by applying them to the task of radio modulation recognition. Results show that radio modulation recognition is not limited by network depth and further work should focus on improving learned synchronization and equalization.
Nathan E. West, Timothy J. O'Shea
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Modulation of Pathogen Recognition by Autophagy [PDF]
Frontiers in Immunology, 2012 Autophagy is an ancient biological process for maintaining cellular homeostasis by degradation of long-lived cytosolic proteins and organelles. Recent studies demonstrated that autophagy is availed by immune cells to regulate innate immunity. On the one hand, cells exert direct effector function by degrading intracellular pathogens; on the other hand ...
Oh, Ji Eun, Lee, Heung Kyu
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Deep Learning for Recognition of Digital Modulations: A Detailed Study [PDF]
AUT Journal of Electrical Engineering, 2022 The automatic modulation recognition of the received signal is very attractive in both military and civilian applications. In the recent years, deep learning techniques have received much attention due to their excellent performance in signal, audio ...
MohammadMohsen Jadidi, Abbas Mohammadi
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Bidirectional Modulation of Recognition Memory [PDF]
The Journal of Neuroscience, 2015 Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks.
Jonathan W. Ho +6 more
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A survey of deep learning based modulation recognition
Dianxin kexue, 2021 Modulation recognition is one of the fundamental tasks for communications systems, which can be widely applied in various fields, such as cognitive radio, intelligent communications, radio surveillance, electronic warfare, etc.In recent years, deep ...
Shujun SUN +3 more
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Contextual Modulation of Biases in Face Recognition [PDF]
PLoS ONE, 2010 The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all ...
Fatima Maria Felisberti, Louisa Pavey
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