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Revised architecture for automatic modulation recognition
International Journal of Information Technology, 2019Cognition and adaptability is a prominent aspect of Communication Intelligence (COMINT). Automatic Modulation Recognition (AMR) is one such aspect. AMR focuses on identifying modulation technique used at a particular carrier frequency which is got by spectral analysis (SA).
Sunil S. Mathad, C. Vijaya
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Modified Automatic Modulation Recognition Algorithm
2009 5th International Conference on Wireless Communications, Networking and Mobile Computing, 2009The modulation identification algorithm proposed by Asoke K. Nandi and E. E. Azzouz is one of the important methods in modulation identification field. A solution to the problem you may meet in realizing this algorithm is presented in this paper. A few modifications are made to the identification parameters gamma_max, sigma_ap and sigma_dp.
Jie Yang, Xumeng Wang, Hongli Wu
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Automatic Modulation Recognition with Deep Learning Algorithms
2024 32nd Signal Processing and Communications Applications Conference (SIU)In this study, an automatic modulation classifier based on Convolutional Neural Network (CNN) was developed using deep learning algorithms. A synthetic dataset generated with GNU Radio consisting of eleven modulations at varying signal-to-noise ratios was used for classification. The time-frequency domain images of the complex signals are generated. An
Çamlıbel, Ayşenur +2 more
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On properties of modulation spectrum for robust automatic speech recognition
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), 2002We report on the effect of band-pass filtering of the time trajectories of spectral envelopes on speech recognition. Several types of filter (linear-phase FIR, DCT, and DFT) are studied. Results indicate the relative importance of different components of the modulation spectrum of speech for ASR.
Noboru Kanedera +2 more
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The modulation spectrum in the automatic recognition of speech
1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings, 2002The article questions the reliability of the short term spectral envelope as the dominant carrier of the phonetic identity of a given speech instant and suggests the temporal dynamics of components of the spectral envelopes as more reliable means for deriving the linguistic context of the speech message.
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Sparsely Connected CNN for Efficient Automatic Modulation Recognition
IEEE Transactions on Vehicular Technology, 2020This paper proposes a convolutional neural network (CNN), called SCGNet, for low-complexity and robust modulation recognition in intelligent communication receivers. Principally, the network combines two types of sparse convolutional layers–depthwise and regular grouped in an architecture to achieve high recognition accuracy while keeping the network ...
Godwin Brown Tunze +3 more
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An adaptive neural network approach for automatic modulation recognition
2017 51st Annual Conference on Information Sciences and Systems (CISS), 2017This paper presents a novel adaptive approach to automatic modulation recognition (AMR) using artificial neural networks (ANN). Two types of features have been combined to ensure the robustness of detection for all types of modulations. An adaptive system of feature extraction and neural network is designed to distinguish the target modulation between ...
Yasaman Ettefagh +2 more
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Automatic Modulation Recognition: An FPGA Implementation
IEEE Communications Letters, 2022Satish Kumar +2 more
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Automatic Generation of Modules of Visual Recognition
Applied Mechanics and Materials, 2013We consider the problem of automatic generation of visual recognition modules. In particular, we consider a self-learning algorithm for visual recognition and system of automatic generation that based on some biological observations.
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Automatic Modulation Recognition Using Deep Learning Architectures
2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2018In this paper, we present an automatic modulation recognition framework for the detection of radio signals in a communication system. The framework considers both a deep convolutional neural network (CNN) and a long short term memory network. Further, we propose a pre-processing signal representation that combines the in-phase, quadrature and fourth ...
Meng Zhang +3 more
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