Results 11 to 20 of about 72,581 (258)
Applied Artificial Intelligence, 2022 In recent years, with the advancement of classical signal processing approaches, numerous works have been performed on the automatic ECG detection schemes for the enhancement of the effectiveness of the identification of the type of ECG heartbeats.
Sampath A, Sumithira T. R
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Current Developments of Sparse Microwave Imaging
Leida xuebao, 2014 The sparse microwave imaging combines the sparse signal processing theory with radar imaging to obtain new theory, new system, and new methodology of microwave imaging.
Wu Yi-rong +5 more
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A novel sparse representation algorithm for AIS real-time signals
EURASIP Journal on Wireless Communications and Networking, 2018 Sparse representation of signals based on a redundant dictionary is a new signal representation theory. Recent research activities in this field have concentrated mainly on the study of dictionary design and sparse decomposition algorithms.
Shuaiheng Huai, Shufang Zhang
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Asynchronous processing of sparse signals
IET Signal Processing, 2014 Unlike synchronous processing, asynchronous processing is more efficient in biomedical and sensing networks applications as it is free from aliasing constraints and quantization error in the amplitude, it allows continuous–time processing and more importantly data is only acquired in significant parts of the signal. We consider signal decomposers based
Azime Can-Cimino +2 more
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A DCA‐based sparse coding for video summarization with MCP
IET Image Processing, 2023 Video summarization offers a summary version that conveys the primary information of a longer video. The main challenges of video summarization are related to keyframe extraction and saliency mapping.
Yujie Li +3 more
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Sparse Signal Representations of Bearing Fault Signals for Exhibiting Bearing Fault Features
Shock and Vibration, 2016 Sparse signal representations attract much attention in the community of signal processing because only a few coefficients are required to represent a signal and these coefficients make the signal understandable.
Wei Peng +3 more
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Perspectives on Theories and Methods of Structural Signal Processing
Leida xuebao, 2015 Over the past decade structural signal processing is an emerging field, which gained researchers' intensive attentions in various areas including the applied mathematics, physics, information theory, signal processing, and so on.
Li Lian-lin, Zhou Xiao-yang, Cui Tie-jun
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Efficient sparse coding in early sensory processing: lessons from signal recovery. [PDF]
PLoS Computational Biology, 2012 Sensory representations are not only sparse, but often overcomplete: coding units significantly outnumber the input units. For models of neural coding this overcompleteness poses a computational challenge for shaping the signal processing channels as ...
András Lörincz +2 more
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Kinetically Consistent Data Assimilation for Plant PET Sparse Time Activity Curve Signals
Frontiers in Plant Science, 2022 Time activity curve (TAC) signal processing in plant positron emission tomography (PET) is a frontier nuclear science technique to bring out the quantitative fluid dynamic (FD) flow parameters of the plant vascular system and generate knowledge on crops ...
Nicola D'Ascenzo +9 more
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Sparse Deconvolution Using Support Vector Machines
EURASIP Journal on Advances in Signal Processing, 2008 Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them ...
Aníbal R. Figueiras-Vidal +5 more
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