Robust detection of neural spikes using sparse coding based features

DOI10.3934/mbe.2020235zbMath1467.92047OpenAlexW3035016037WikidataQ100312550 ScholiaQ100312550MaRDI QIDQ2038824

Xiao-Tian Wang, Quan Yuan, Zuozhi Liu

Publication date: 7 July 2021

Published in: Mathematical Biosciences and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/mbe.2020235

zbMATH Keywords

sparse representationdictionary learningneural spike detectionsparse feature

Mathematics Subject Classification ID

Neural biology (92C20)

Uses Software

• PDCO
• AS 136

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
• Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit
• Pose-robust face recognition via sparse representation
• Atomic Decomposition by Basis Pursuit
• Sparse and Redundant Representations
• Hyperspectral Image Super-Resolution via Non-Negative Structured Sparse Representation
• Off-the-Grid Line Spectrum Denoising and Estimation With Multiple Measurement Vectors
• Matching pursuits with time-frequency dictionaries
• On amplitude and frequency demodulation using energy operators
• Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization

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