Yayıncı "IEEE" Elektrik-Elektronik Mühendisliği Bölümü Koleksiyonu için listeleme
Toplam kayıt 14, listelenen: 1-14
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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 ... -
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 ... -
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
(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 ... -
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 ... -
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, ... -
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. ... -
Sequential Combinations of Multiple Adaptive Lattice Filters in Cognitive Radio Channel Identification
(IEEE, 2017)Sequential convex combinations of multiple adaptive lattice filters using different exponential weighting factors in cognitive radio channel identification framework have been considered in this presentation. First, the ...