Machine health monitoring based on locally linear embedding with kernel sparse representation for neighborhood optimization

Computer Science

• Embedding 100%
• Sparse Representation 100%
• Relationships 33%
• Related Feature 33%
• Dimensionality Reduction 33%
• Vectors 33%
• Feature Extraction 33%
• Feature Space 33%
• Kernel Function 33%
• Connection Weight 33%
• Nonlinear System 33%
• Feature Fusion 33%
• Dimensional Vector Space 33%
• Dimensional Surface 33%
• Represent Data 33%
• locality preserving projection 33%

Mathematics

• Neighbourhood 100%
• Manifold 100%
• Weights 42%
• Number 14%
• Variations 14%
• Data Point 14%
• Adaptability 14%
• System State 14%
• Projection 14%
• Nonlinear System 14%
• Dimensionality Reduction 14%
• Feature Space 14%
• Vector Space 14%
• Dimensional Vector Space 14%
• Dimensional Surface 14%