Results 91 to 100 of about 256,514 (313)
The behaviour of the Lee-McClellan algorithms for the signal reconstruction
, 2022 A complex signal is in general not uniquely defined by its phase. However a set of conditions have been developed for a complex signal in which a discrete time-domain sequence is completely specified by its phase (Lee and McClellan, 1997).
Protzmann, M., Boche, H.
core
Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini +28 more
wiley +1 more source
Compressed sensing subspace pursuit algorithm based on two stagewise weak selection
Dianxin kexue, 2020 Compressed sensing is a new way of signal sampling and data compression.The subspace pursuit algorithm has higher efficiency and precision in the compressed sensing reconstruction algorithms,but it needs the sparsity of the signal as a priori information.
Bowei WANG, Jin TAN
doaj
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Retrograde trans‐synaptic degeneration (rTSD) from posterior visual pathway lesions in multiple sclerosis (MS) is characterized by hemi‐macular ganglion cell‐inner plexiform layer (GCIPL) thinning and contralateral visual field loss.
Abdul Jaber Tayem +17 more
wiley +1 more source
The use of side information in Compressive Sensing: Measurement design and signal reconstruction [PDF]
, 2016 We study the problem of sparse signal acquisition and reconstruction known as Compressive Sensing (CS) in the presence of side information, i.e., a class of signals correlated with the target signal.
De Castro Mota, J +3 more
core
Reconstruction of a Signal from the Real Part of Its Discrete Fourier Transform [Tips & Tricks]
, 2018 In this tutorial, we present a procedure for reconstructing a complex-valued, discrete-time signal from only partial Fourier transform (FT) information, more specifically, the real part of its discrete FT (RDFT).
So, Stephen +3 more
core +1 more source
Combinatorial Regression and Improved Basis Pursuit for Sparse Estimation [PDF]
, 2012 Sparse representations accurately model many real-world data sets. Some form of sparsity is conceivable in almost every practical application, from image and video processing, to spectral sensing in radar detection, to bio-computation and genomic signal ...
Khajehnejad, M. Amin
core +1 more source
Signal Reconstruction Using Determinantal Sampling
Applied and Computational Harmonic AnalysisWe study the approximation of a square-integrable function from a finite number of evaluations on a random set of nodes according to a well-chosen distribution. This is particularly relevant when the function is assumed to belong to a reproducing kernel Hilbert space (RKHS).
Ayoub Belhadji +2 more
openaire +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang +8 more
wiley +1 more source
Efficient multiresolution signal coding via a signal-adapted perfect reconstruction filter pyramid
, 1991 Consideration is given to the problem of designing a signal-adapted two-band filtering system that has the perfect reconstruction property for application to multiresolution signal coding.
Macq, Benoît +3 more
core +1 more source