Constrained polynomial matrix zonotopes enable algebraically exact set propagation for data-driven reachability analysis of linear and polynomial systems without over-approximation.
Constrained zonotopes: A new tool for set-based estimation and fault detection
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Set-based training of neural barrier certificates uses a loss function that encodes all safety properties so that zero loss formally proves the certificate is valid, collapsing iterative training and verification into one procedure.
Constrained matrix convex generators bridge data-driven reachability and statistical estimation by providing minimum-volume uncertainty sets that coincide with Gaussian maximum-likelihood ellipsoids and remain tighter than matrix zonotopes for mixed noise.
Row-norm-minimizing right inverse via SOCP plus A-optimal input design within the constrained matrix zonotope framework reduces conservatism in data-driven reachable sets for linear and piecewise-affine systems.
citing papers explorer
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Data-Driven Nonconvex Reachability Analysis using Exact Set Propagation
Constrained polynomial matrix zonotopes enable algebraically exact set propagation for data-driven reachability analysis of linear and polynomial systems without over-approximation.
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Set-Based Training of Neural Barrier Certificates for Safety Verification of Dynamical Systems
Set-based training of neural barrier certificates uses a loss function that encodes all safety properties so that zero loss formally proves the certificate is valid, collapsing iterative training and verification into one procedure.
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Bridging Data-Driven Reachability Analysis and Statistical Estimation via Constrained Matrix Convex Generators
Constrained matrix convex generators bridge data-driven reachability and statistical estimation by providing minimum-volume uncertainty sets that coincide with Gaussian maximum-likelihood ellipsoids and remain tighter than matrix zonotopes for mixed noise.
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Data-Driven Reachability Analysis with Optimal Input Design
Row-norm-minimizing right inverse via SOCP plus A-optimal input design within the constrained matrix zonotope framework reduces conservatism in data-driven reachable sets for linear and piecewise-affine systems.