Kategori "Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı" Elektrik-Elektronik Mühendisliği Bölümü Koleksiyonu İçin Listeleme
Toplam kayıt 26, listelenen: 1-20
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Adaptive Multichannel Sequential Lattice Prediction Filtering Method For Cognitive Radio Spectrum Sensing in Subbands
(IEEE, 2012)A multichannel characterization for autoregressive moving average(ARMA) spectrum estimation in subbands with applications to cognitive radio spectrum sensing is considered in this presentation. The fullband ARMA spectrum ... -
Adaptive Multichannel Sequential Lattice Prediction Filtering Method for Range Estimation in Cognitive Radios
(IEEE, 2014)A range estimation method 14 cognitive MIMO-OFDM radio systems is considered in this presentation. The range estimation problem is formulated as time delay estimation problem, and then adapted as multiple channel estimation ... -
Adaptive V-BLAST Type Channel Equalizer Design for Cognitive MIMO-OFDM Radios
(IEEE, 2013)A channel shortening equalizer design for cognitive Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) communication systems is considered in this presentation. The proposed receiver ... -
Analysis of EEG Signals by Emprical Mode Decomposition and Mutual Information
(IEEE, 2013)Empirical mode decomposition has been recently proposed to analyze non-stationary signals. It decomposes the signal into intrinsic mode functions (IMF) which are derived from the signal itself. However, it is still an ... -
Breast Cancer Classification by Using Support Vector Machines with Reduced Dimension
(Croatian Society Electronics Marine, 2011)Correct and timely diagnosis of diseases is an essential matter in medical field. Limited human capability and limitations decrease the rate of correct diagnosis. Machine learning algorithms such as support vector machine ... -
Combination of Approximate l(0)-Norm Regularized Multiple Adaptive Lattice Filters in Sparse Cogntive Radio Coannel Identification
(IEEE, 2020)A priori recursive least squares (RLS) lattice algorithm has been regularized by adding an approximation of 10-norm constraint penalty term to the cost function so as to introduce sparsity awareness to the prenously proposed ... -
Combination of Approximate P0-Norm Regularized Multiple Adaptive Lattice Filters in Sparse Cognitive Radio Channel Identification
(Institute of Electrical and Electronics Engineers Inc., 2020)A priori recursive least squares (RLS) lattice algorithm has been regularized by adding an approximation of ?0-norm constraint penalty term to the cost function so as to introduce sparsity awareness to the previously ... -
Combinations of Multiple Adaptive Lattice Filters in Sparse Cognitive Radio Channel Identification
(IEEE, 2019)Sparsity awareness feature has been introduced into the a priori recursive least squares (RLS) lattice algorithm by regularizing the RLS cost function with the addition of l(1)-norm constraint penalty term. The newly ... -
Compression of hyperspectral images using adaptive luminance transform
(Institute of Electrical and Electronics Engineers Inc., 2018)In this paper, compression of hyperspectral images with luminance transform is explained. First, similar image bands are grouped on hyperspectral image and luminance transform is performed independently on these groups. ... -
Compression of Hyperspectral Images using Adaptive Luminance Transform
(IEEE, 2018)In this paper, compression of hyperspectral images with luminance transform is explained. First, similar image bands are grouped on hyperspectral image and luminance transform is performed independently on these groups. ... -
Detrended Fluctuation Analysis For Empirical Mode Decomposition Based Denoising
(IEEE, 2014)Empirical mode decomposition (EMD) is a recently proposed method to analyze non-linear and non-stationary time series by decomposing them into intrinsic mode functions (IMFs). One of the most popular application of such a ... -
Development of a Brushless DC (BLDC) Motor Driven Retractable Sonar Antenna (RESA) System Design by means of Hydrodynamic Analysis
(Institute of Electrical and Electronics Engineers Inc., 2021)In the early stage of design of the crane structure of retractable sonar antenna systems extended from the hull of a ship, hydrodynamic analysis of the sonar geometry is required. Based on the information obtained by the ... -
ECG signal analysis based on variational mode decomposition and bandwidth property
(IEEE, 2016)In this paper, the bandwidth properties of the modes obtained using the variational mode decomposition (VMD) are analyzed to detect arrhythmia electrocardiogram (ECG) beats. The VMD is an enhanced version of the empirical ... -
Effect of temperature and graphene oxide on the swelling of PAAm-GO composite gels
(Avestia Publishing, 2019)Graphene oxide (GO) is a two dimensional carbon material with similar one-atom thickness, and is a light material having extremely high strength and thermal stability [1]. Thus, GO is an efficient filler for the enhancement ... -
Effects of Hyperspectral Image Compression Methods on Classification
(IEEE, 2018)Because of having large data size in hyperspectral imaging, compression becomes an important necessity in terms of the transmission and storage of the data. There are several compression approaches proposed in the literature, ... -
Effects of hyperspectral image compression methods on classification
(Institute of Electrical and Electronics Engineers Inc., 2018)Because of having large data size in hyperspectral imaging, compression becomes an important necessity in terms of the transmission and storage of the data. There are several compression approaches proposed in the literature, ... -
EOG denoising using empirical mode decomposition and detrended fluctuation analysis
(IEEE, 2014)In this study, a method is presented for the removal of electrooculogram (EOG) noise from electroencephalography (EEG) recordings by using recently proposed data driven approach called Empirical Mode Decomposition (EMD). ... -
Epilepsy detection using Empirical Mode Decomposition and detrended Fluctuation Analysis
(IEEE, 2015)In this study, a new method is presented to analyze electroencephalography (EEG) signals by deploying recently proposed adaptive and data driven signal processing method called Empirical Mode Decomposition (EMD). The EMD ... -
Hilbert-Huang Transform Based Hierarchical Clustering For Eeg Denoising
(IEEE, 2013)Empirical mode decomposition (EMD) is a recently introduced decomposition method for non-stationary time series. The sum of the decomposed intrinsic mode functions (IMF) can be used to reconstruct the original signal. ...