Results 131 to 140 of about 154,546 (314)
Three-dimensional sparse recovery space-time adaptive processing for airborne radar
The Journal of Engineering, 2019 Conventional 3-dimensional (3D) space-time adaptive processing (STAP) has achieved good performance for non-stationary clutter suppression. However, the performance of 3D STAP rapidly degrades when applied to heterogeneous clutter environment due to the ...
Keqing Duan +4 more
doaj +1 more source
Advanced Functional Materials, EarlyView.Multiscale experiments and modeling reveal how Ti3C2Tx MXene nanosheets reinforce PVDF nanocomposites. An optimal MXene loading (∼1 wt.%) nearly doubles tensile strength through efficient stress transfer, flake alignment, and crack‐deflection mechanisms, transforming ductile polymer behavior into a controlled multi‐stage fracture pathway which aligns ...
Bita Soltan Mohammadlou +5 more
wiley +1 more source
MIMO High Frequency Surface Wave Radar Using Sparse Frequency FMCW Signals
International Journal of Antennas and Propagation, 2017 The heavily congested radio frequency environment severely limits the signal bandwidth of the high frequency surface wave radar (HFSWR). Based on the concept of multiple-input multiple-output (MIMO) radar, we propose a MIMO sparse frequency HFSWR system ...
Mengguan Pan, Baixiao Chen
doaj +1 more source
Deep Neural Network Structured Sparse Coding for Online Processing
IEEE Access, 2018 Sparse coding, which aims at finding appropriate sparse representations of data with an overcomplete dictionary set, has become a mature class of methods with good efficiency in various areas, but it faces limitations in immediate processing such as real-
Haoli Zhao +3 more
doaj +1 more source
, 2011 This paper introduces the class of ambiguity sparse processes, containing subsets of popular nonstationary time series such as locally stationary, cyclostationary and uniformly modulated processes. The class also contains aggregations of the aforementioned processes.
openaire +2 more sources
, 2005 In order to perform many signal processing tasks such as classification,pattern recognition and coding, it is helpful to specify a signal model interms of meaningful signal structures. In general, designing such a modelis complicated and for many signals
Blumensath, Thomas
core
Variational semi-blind sparse deconvolution with orthogonal kernel bases and its application to MRFM [PDF]
, 2014 We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known.
Se Un Parka +5 more
core +1 more source
Advanced Functional Materials, EarlyView.Here, SubNc single‐component organic photodiodes (SC‐OPDs) are investigated, which achieve highly competitive performance metrics, including high EQE, ultra‐low JD, and high specific detectivity (D*). This study emphasizes the critical role of an organic buffer layer in studying the interface energetics and effects to achieve state‐of‐the‐art ...
Anncharlott Kusber +12 more
wiley +1 more source
Advanced Functional Materials, EarlyView.A bilayer “Anchor‐and‐Seal” passivation strategy using EDAI2 and 4MeO‐PEAI effectively mitigates surface defects in vacuum‐processed perovskite films through synergistic hydrogen bonding and Lewis base coordination. This approach optimizes interfacial energy alignment and suppresses non‐radiative recombination, enabling vacuum‐deposited p‐i‐n ...
Mohammadhossein Kohan +4 more
wiley +1 more source
Sparse linear predictors for speech processing [PDF]
Interspeech 2008, 2008 Giacobello, Daniele +4 more
openaire +2 more sources