A regularized formulation for time-limited H2 model reduction from noisy impulse responses yields lower errors than unregularized alternatives on SLICOT benchmarks.
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Data-Driven Regularized Time-Limited h2 Model Reduction from Noisy Impulse Responses
A regularized formulation for time-limited H2 model reduction from noisy impulse responses yields lower errors than unregularized alternatives on SLICOT benchmarks.