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Amplitude and Frequency Modulations with Cellular Neural Networks
(Springer, 2015)
Amplitude and frequency modulations are still the most popular modulation techniques in data transmission at telecommunication systems such as radio and television broadcasting gsm etc. However the architectures of these ...
Information theoretical performance limits of single-carrier underwater acoustic systems
(Inst Engineering Technology-IET, 2014)
In this study the authors investigate the information theoretical limits on the performance of point-to-point single-carrier acoustic systems over frequency-selective underwater channels with intersymbol interference. Under ...
Joint Channel Estimation Equalization and Data Detection for OFDM Systems in the Presence of Very High Mobility
(IEEE-INST Electrical Electronics Engineers Inc, 2010)
This paper is concerned with the challenging and timely problem of joint channel estimation equalization and data detection for uplink orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency ...
Nondata-aided joint channel estimation and equalization for OFDM systems in very rapidly varying mobile channels
(IEEE-INST Electrical Electronics Engineers Inc, 2012)
This paper is concerned with the challenging and timely problem of joint channel estimation and equalization for orthogonal frequency division multiplexing (OFDM) systems in the presence of frequency selective and very ...
Bayesian estimation of discrete-time cellular neural network coefficients
(TUBITAK Scientific & Technical Research Council Turkey, 2017)
A new method for finding the network coefficients of a discrete-time cellular neural network (DTCNN) is proposed. This new method uses a probabilistic approach that itself uses Bayesian learning to estimate the network ...
A low-complexity time-domain MMSE channel estimator for space-time/frequency block-coded OFDM systems
(Hindawi Publishing Corporation, 2006)
Focusing on transmit diversity orthogonal frequency-division multiplexing (OFDM) transmission through frequency-selective channels this paper pursues a channel estimation approach in time domain for both space-frequency ...
Linear expansions for frequency selective channels in OFDM
(Elsevier GMBH Urban & Fischer Verlag, 2006)
Modeling the frequency selective fading channels as random processes we employ a linear expansion based on the Karhumen-Loeve (KL) series representation involving a complete set of orthogonal deterministic vectors with a ...
A low-complexity KL expansion-based channel estimator for OFDM systems
(2005)
This paper first proposes a computationally efficient pilot-aided linear minimum mean square error (MMSE) batch channel estimation algorithm for OFDM systems in unknown wireless fading channels. The proposed approach employs ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...