[PDF] Top 20 Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing
Has 10000 "Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing" found on our website. Below are the top 20 most common "Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing".
Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing
... LO signal leaks into the mixer input port, it self-mixes down to baseband causing interfering sig- nal components at zero ...satisfactory receiver performance, some compensation of the DC offsets is ... See full document
11
MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization
... has been engaged in research on signal processing, microphone array, and blind source separation (BSS). More specifically, he is working on the frequency-domain BSS for acoustic convolutive ... See full document
12
Factors Affecting Performance of GPS Receiver and Solutions for Sustainable Signal
... post processing algorithm increases the precision of distance measurement between two clusters and the location co- ordinates can be used in assisting other GPS ...lowering receiver noise at the same ... See full document
12
Relevance of polynomial matrix decompositions to broadband blind signal separation
... of signal decompositions and matrix factorisations, and address statistical dependence, periodi- city, spectral shape, time coherence or smoothness [5 – ...above signal decompositions are based on an ... See full document
11
Nonlinear Blind Source Separation for EEG Signal Pre processing in Brain Computer Interface System for Epilepsy
... of signal processing and analysis of EEG waveforms based on computer encouraged the scientists in their work ...data based on ICA as a feature extraction technique, and on evolving fuzzy ... See full document
8
A wireless MIMO CPM system with blind signal separation for incoherent demodulation
... CPM receiver in Zhao and Giannakis (2005) the perfect knowledge of the MIMO channel is ...the receiver is questionable as training based chan- nel estimation is not applicable for MIMO CPM ... See full document
5
An ensemble learning algorithm for blind signal separation problem
... is based on the assumptions that the quantities of interest are governed by probability distributions, and that optimal decisions can be made by reasoning about these probabilities together with the ...approach ... See full document
5
DME interference suppression algorithm based on signal separation estimation theory for civil aviation system
... power signal, DME interference could lead to acquisition and tracking failure of a GPS ...original signal and the suppressed signal with the proposed method are demonstrated in ...GPS signal ... See full document
8
Separation algorithm of vital sign signal in complex environments based on time frequency filtering
... reflected signal is phase- modulated due to the chest movements associated with breathing and ...life signal frequency from the change of reflected wave by applying appropriate ... See full document
10
Independent vector analysis based on overlapped cliques of variable width for frequency-domain blind signal separation
... mel-scales based on the measured correlation coefficients between different frequency ...source separation performance and faster convergence to correct solutions owing to more accurate modeling of ... See full document
12
A study of blind source separation using nonnegative matrix factorization
... is based on the concept of audio or sound ...the separation of speech from the ...source signal as well as features simple algorithm, fast speed, and real-time data ... See full document
7
Performance of Entropy Based on Generalized Laplace Function For Blind Signal Separation
... Blind signal separation is the problem of estimating a set of source signals from their mixture without prior knowledge about the source ...of signal independence in the problem of ... See full document
9
Blind source separation with optimal transport non negative matrix factorization
... Noise data. For the speech denoising experiment, we consider 4 types of noises: cicadas, drums, subway, and sea. For each, we gathered one file for training and one file for testing from non-copyrighted sources on the ... See full document
16
Blind Spectrum Sensing Algorithm Based on Blind Signal Separation in Cognitive Radar
... PU signal is present, both signal statistics q 1 and q 2 have a large ...PU signal is present, and one of the separated signals consists of noise only, signal statistic q ... See full document
6
Blind Signal Processing in Telecommunication Systems Based on Polynomial Statistics
... the blind identification problem is reduced to the problem of solving the systems of polynomial equations over multiple ...approach based on the use of polyspectrums (so-called higher-order statistics ... See full document
9
Generalized independent low rank matrix analysis using heavy tailed distributions for blind source separation
... ILRMA based on the Gaussian ...poor separation results except for t-ILRMA in ...mixture signal by ignoring the important components for discriminating the sources, and the esti- mated signals become ... See full document
25
Blind Source Separation Combining Independent Component Analysis and Beamforming
... of blind source separation (BSS) on a microphone array combining subband independent component analysis (ICA) and ...section based on the estimated DOA, and (3) integration of (1) and (2) ... See full document
12
Blind non-intrusive appliance load monitoring using graph-based signal processing
... novel, blind, unsupervised low-rate NALM ...problems. Based on the results from two datasets, our unsupervised GSP-based NALM approach performs as well as the supervised GSP-based NALM ... See full document
5
Blind non-intrusive appliance load monitoring using graph-based signal processing
... novel, blind, unsupervised low-rate NALM ...problems. Based on the results from two datasets, our unsupervised GSP-based NALM approach performs as well as the supervised GSP-based NALM ... See full document
5
Error bounds of block sparse signal recovery based on q ratio block constrained minimal singular values
... there are block NSP and block RIP to characterize the measurement matrix in order to guarantee a successful recovery through (1) [16]. Nevertheless, they are still com- putationally hard to be verified for a given A. ... See full document
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