Results 221 to 230 of about 178,865 (261)

Modulation classification in unknown dispersive environments

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
The problem of distinguishing reliably between signaling formats in the presence of noise, interference, unknown dispersive channel conditions, as well as timing and frequency mismatches is addressed. Methods based on a combination of blind equalization and universal classification are presented and their performance is assessed through simulations.
Bernd-Peter Paris, Geoffrey C. Orsak, Hongda Chen, Nirmal Warke   +3 more
openaire   +1 more source

LSTM-based Automatic Modulation Classification

2020 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), 2020
Recently, automatic modulation classification (AMC) has been studied by more and more researchers, and a host of methods based on deep learning have been proposed. Different from image data, signal data is a sequence that changes with time, and has temporal characteristics. Like the spatial feature, the temporal feature cannot be ignored. In this paper,
Quan Zhou 0008, Xiaojun Jing, Yuan He 0009, Yuanhao Cui, Michel Kadoch, Mohamed Cheriet   +5 more
openaire   +2 more sources

Performance Analysis of Modulation Classification with a Preprocessing

2020 International Conference on Information and Communication Technology Convergence (ICTC), 2020
In this paper, we propose a preprocessing method for automatic modulation classification that allows reliable classification of the digital baseband modulation schemes whose signal constellations have symmetry about the in-phase and quadrature axes. The proposed preprocessing is used to generate additional data for modulation classification based on ...
Seongjin Ahn, Dongweon Yoon, Hongsuk Shim, Sungkyun Park   +3 more
openaire   +2 more sources

OFDM Modulation Classification and Parameters Extraction

2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2006
A novel comprehensive classification system is proposed for recognizing the orthogonal frequency division multiplexing (OFDM) signal and extracting its parameters. An empirical distribution function -based Gaussianity test technique is first applied to distinguish OFDM from single carrier modulations.
Hong Li 0011, Yeheskel Bar-Ness, Ali Abdi, Oren Somekh, Wei Su 0001   +4 more
openaire   +1 more source

Classification of digital modulations by MCMC sampling

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
This paper addresses the problem of classification of digital modulations. The proposed solution uses the Bayes classifier, which is implemented by the Markov chain Monte Carlo scheme. The implementation considers classifications in the presence of phase and frequency offsets as well as residual filtering effects coming from imperfect channel ...
Stéphane Lesage, Jean-Yves Tourneret, Petar M. Djuric   +2 more
openaire   +2 more sources

Image Classification Based on IndCRNN Module

Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing, 2020
As a core of computer vision, image classification has become a hot topic in recent years. RNN framework can not only model sequence data, predict the trend of sequence data, but also show good results in image classification. In this paper, an improved model IndCRNN is proposed for the over-fitting phenomenon of Independent Recurrent Neural Network ...
openaire   +2 more sources

Real-Time Automatic Modulation Classification

2019 International Conference on Field-Programmable Technology (ICFPT), 2019
Deep learning based techniques have shown promising results over traditional hand-crafted methods for automatic modulation classification for radio signals. However, implementation of these deep learning models on specialized hardware can be challenging, as both latency and throughput performance are critical to achieving real-time response to over-the-
Stephen Tridgell, David Boland, Philip H. W. Leong, Siddhartha 0003   +3 more
openaire   +1 more source

Modulation Classification In Multipath Fading Environments

2007 4th International Symposium on Wireless Communication Systems, 2007
A new approach to classification of MQAM/MPSK signals in multipath fading environments is presented The proposed approach, in which the two-step equalization strategy and higher-order cumulants based classifier are adopted, can effectively classify the MPSK and high-order QAM signals.
Lin Yang, Zhi Ji, Xiaodong Xu 0004, Xuchu Dai, Peixia Xu   +4 more
openaire   +1 more source

Automatic classification of analog modulation schemes

2012 IEEE Radio and Wireless Symposium, 2012
This paper discusses automatic modulation classification (AMC) of analog schemes. Histograms of instantaneous frequency are used as classification features and Support Vector Machines (SVMs) are then applied to classify the unknown modulation schemes. This novel machine-learning based method can insure robustness in a wide range of SNR.
Haifeng Xiao, Yun Q. Shi 0001, Wei Su 0001, John A. Kosinski   +3 more
openaire   +2 more sources

Multi-module Image Classification System

2006
In this paper, we propose an image classification system employing multiple modules. The proposed system hierarchically categorizes given sports images into one of the predefined sports classes, eight in this experiment. The image first categorized into one of the two classes in the global module. The corresponding local module is selected accordingly,
Wonil Kim, Sangyoon Oh 0001, Sanggil Kang, Dongkyun Kim   +3 more
openaire   +2 more sources