Results 221 to 230 of about 97,815 (271)

Automatic modulation recognition—I

Journal of the Franklin Institute, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Azzouz, E. E., Nandi, A. K.
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Automatic analogue modulation recognition

Signal Processing, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nandi K. Nandi, Elsayed Elsayed Azzouz
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An effective algorithm for automatic modulation recognition

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
Based on the previous studies, this article proposes an effective modulation recognition algorithm which is a combination of Higher Order Cumulants (HOC) and Continues Wavelet Transform (CWT). In the Additive White Gaussian Noise (AWGN) the identification of QAM16, QAM32, QAM64, BPSK, QPSK and PSK8 types of modulation were almost successful.
Saeed Ghasemi, Ali Gangal
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Automatic modulation type recognition

Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341), 2002
Identification of the modulation type of a received signal is a problem encountered in radio spectrum surveillance and control. It is attractive to design methods that use only one or two time-domain classification parameters, in order to minimize the computational complexity.
I. Druckmann, E.I. Plotkin, M.N.S. Swamy
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Automatic modulation recognition of digitally modulated signals

IEEE Military Communications Conference, 'Bridging the Gap. Interoperability, Survivability, Security', 2003
A modulation recognizer that automatically reports modulation types of constant-envelope modulated signals is developed using zero-crossing techniques. The zero-crossing sampler, as a signal conditioner, has the advantage of providing accurate phase transition information over a wide dynamic frequency range.
S.-Z. Hsue, S.S. Soliman
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Automatic Modulation Recognition Based on Morphological Operations

Circuits, Systems, and Signal Processing, 2013
Automatic modulation recognition under negative signal-to-noise ratio (SNR) environment is a challenging topic. In this paper, we propose the method consisting of two main steps: constructing a template library and recognition. The former extracts the morphological envelope of each signal power spectrum by using the morphological close–open operation ...
Yuan Zhang, Xiurong Ma, Duo Cao
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Comprehensive modulation representation for automatic speech recognition

Interspeech 2005, 2005
We present a new feature representation for speech recognition based on both amplitude modulation spectra (AMS) and frequency modulation spectra (FMS). A comprehensive modulation spectral (CMS) approach is defined and analyzed based on a modulation model of the band-pass signal.
Wang, Yadong, Greenberg, Steven, Swaminathan, Jayaganesh, Kumaresan, Ramdas, Poeppel, David   +4 more
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Algorithms for automatic modulation recognition of communication signals

IEEE Transactions on Communications, 1998
This paper introduces two algorithms for analog and digital modulations recognition. The first algorithm utilizes the decision-theoretic approach in which a set of decision criteria for identifying different types of modulations is developed. In the second algorithm the artificial neural network (ANN) is used as a new approach for the modulation ...
Asoke Kumar Nandi, Elsayed Elsayed Azzouz   +1 more
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Automatic recognition of digitally modulated communications signals

ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359), 2003
This paper introduces an algorithm that extends the capability of digital modulations classifiers to cope with signals that have memory incorporated in their modulation scheme. The algorithm employs the decision-theoretic approach where the identification of different modulation types is performed by developing a set of decision criteria.
V. Ramakomar, Daryoush Habibi, Abdesselam Bouzerdoum   +2 more
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A novel method for automatic modulation recognition

Applied Soft Computing, 2012
Automatic recognition of the digital modulation plays an important role in various applications. This paper investigates the design of an accurate system for recognition of digital modulations. First, it is introduced an efficient pattern recognition system that includes two main modules: the feature extraction module and the classifier module. Feature
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