A sparsification approach to set membership identification of a class of affine hybrid systems

Keyphrases

• Affine 100%
• Affine Model 100%
• Computer Vision Applications 50%
• Convex Relaxation 50%
• Discrete-time 50%
• Dynamic Texture Segmentation 50%
• Experimental Information 50%
• Hybrid System 100%
• Input-output Data 50%
• Minimum number 100%
• Noisy Input 50%
• NP-hard Problem 50%
• Number of Plants 50%
• Performance Criteria 50%
• Robust Identification 50%
• Set-membership 50%
• Set-membership Estimation 100%
• Sparse Signal Recovery 50%
• Sparsification 100%
• Sparsity 50%
• Suitable Set 50%
• Switch number 100%
• Switching Sequence 50%
• Vector Sequences 50%
• Video Dynamics 50%
• Video Shot 50%

Computer Science

• Computer Vision Applications 100%
• Convex Relaxation 100%
• discrete-time 100%
• Finite Collection 100%
• Input/Output 100%
• Performance Criterion 100%
• Priori Information 100%
• Sparsity 100%
• Texture Segmentation 100%

Engineering

• Affine Model 100%
• Computervision 50%
• Discrete Time 50%
• Main Result 50%
• Output Data 50%
• Performance Criterion 50%
• Priori Information 50%
• Sparse Signal 50%
• Sparsity 50%
• Switched Systems 50%
• Switching Sequence 50%
• Texture Segmentation 50%