Results 241 to 250 of about 450,675 (283)

Classification of chitinases modules

1999
Chitinases frequently display a modular structure featuring a catalytic domain attached to one or several ancillary noncatalytic domains whose function is often chitin binding. Gene cloning and DNA sequencing have allowed the determination of a massive number of amino acid sequences of chitinases during the last 10 years.
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Classification of mixed modules

Acta Mathematica Hungarica, 1996
The authors describe a scheme for the classification of mixed modules over a discrete valuation domain \(R\) whose torsion submodule is a direct sum of cyclic modules and whose torsion-free quotient is a vector space over the field of fractions of \(R\).
Mutzbauer, O., Toubassi, E.
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Automatic Modulation Classification using DenseNet

2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP), 2021
Wireless Communication over long distances has revolutionised the way world works, functions and interacts.Modulation of a signal containing information has made all this possible.The identification of modulation type of a signal forms an integral part in several military and civilian applications.While the classical approaches of modulation ...
Sameera Shaik, S. Kirthiga
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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
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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
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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
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Comparison of Automatic Modulation Classification Techniques

Journal of Communications, 2022
The advancement of digital communication and technology triggered new challenges related to the channel and radio spectrum utilization. From the other hand, real-time communications are keen of time where requests need to be processed in very short time.
Salah Ayad Jassim, Ibrahim Khider
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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
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Sequential modulation classification of dependent samples

1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002
We classify the modulation scheme of a received signal waveform modeled by a finite state Markov chain. We compare the likelihood ratio test (LRT) known as a fixed-sample-size classifier, which uses a fixed amount of data, and the sequential probability ratio test (SPRT) known as a fixed-error-rate classifier, which uses a variable amount of data just ...
Yu-Chuan Lin, C.-C. Jay Kuo
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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
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