Lithium-ion battery capacity estimation: a method based on visual cognition

DOI10.1155/2017/6342170zbMath1380.94016OpenAlexW2775097304MaRDI QIDQ1693799

Yujie Cheng, Chao Yang, Laifa Tao

Publication date: 31 January 2018

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/6342170

zbMATH Keywords

decompositionhuman visual system (HVS)high-dimensional feature vectorLaplacian eigenmap manifold learning methodLithium-ion battery capacity estimationmultiple spatial-frequency channelstwo-dimensional imagevisual cognition

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Observability (93B07) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Uses Software

• NSCT toolbox

Cites Work

• Multifocus image fusion using the nonsubsampled contourlet transform
• Using locally estimated geodesic distance to optimize neighborhood graph for isometric data embedding
• Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data

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