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We are concerned with efficient numerical methods for stochastic continuous-time algebraic Riccati equations (SCARE). Such equations frequently arise from the state-dependent Riccati equation approach which is perhaps the only systematic…

Optimization and Control · Mathematics 2024-01-23 Tsung-Ming Huang , Yueh-Cheng Kuo , Ren-Cang Li , Wen-Wei Lin

For large-scale discrete-time algebraic Riccati equations (DAREs) with high-rank nonlinear and constant terms, the stabilizing solutions are no longer numerically low-rank, resulting in the obstacle in the computation and storage. However,…

Numerical Analysis · Mathematics 2021-07-27 Bo Yu , Ning Dong

The structure-preserving doubling algorithm (SDA) is a fairly efficient method for solving problems closely related to Hamiltonian (or Hamiltonian-like) matrices, such as computing the required solutions to algebraic Riccati equations.…

Numerical Analysis · Mathematics 2020-05-19 Zhen-Chen Guo , Eric King-Wah Chu , Xin Liang , Wen-Wei Lin

We consider the large scale nonsymmetric algebraic Riccati equation arising in transport theory, where the $n\times n$ coefficient matrices $B, C$ are symmetric and low-ranked and $A, E$ are rank one updates of nonsingular diagonal…

Numerical Analysis · Mathematics 2014-07-10 Peichang Guo

In \emph{Guo et al, arXiv:2005.08288}, we propose a decoupled form of the structure-preserving doubling algorithm (dSDA). The method decouples the original two to four coupled recursions, enabling it to solve large-scale algebraic Riccati…

Numerical Analysis · Mathematics 2020-11-04 Zhen-Chen Guo , Eric King-Wah Chu , Xin Liang , Wen-Wei Lin

This paper analyzes a special instance of nonsymmetric algebraic matrix Riccati equations arising from transport theory. Traditional approaches for finding the minimal nonnegative solution of the matrix Riccati equations are based on the…

Numerical Analysis · Mathematics 2011-09-26 Chun-Yueh Chiang , Matthew M. Lin

The discrete-time algebraic Riccati equation (DARE) have extensive applications in optimal control problems. We provide new theoretical supports to the stability properties of solutions to the DARE and reduce the convergence conditions…

Optimization and Control · Mathematics 2021-10-25 Chun-Yueh Chiang

This paper introduces a new algorithm for solving large-scale continuous-time algebraic Riccati equations (CARE). The advantage of the new algorithm is in its immediate and efficient low-rank formulation, which is a generalization of the…

Numerical Analysis · Mathematics 2021-05-10 Peter Benner , Zvonimir Bujanović , Patrick Kürschner , Jens Saak

We propose a computationally efficient algorithm that achieves anytime regret of order $\mathcal{O}(\sqrt{t})$, with explicit dependence on the system dimensions and on the solution of the Discrete Algebraic Riccati Equation (DARE). Our…

Machine Learning · Statistics 2026-01-06 Jafar Abbaszadeh Chekan , Cedric Langbort

Algebraic Riccati equations (AREs) have been extensively applicable in linear optimal control problems and many efficient numerical methods were developed. The most attention of numerical solutions is the (almost) stabilizing solution in…

Optimization and Control · Mathematics 2021-11-18 Chun-Yueh Chiang , Hung-Yuan Fan

This paper studies a continuous-time stochastic linear-quadratic (SLQ) optimal control problem on infinite-horizon. A data-driven policy iteration algorithm is proposed to solve the SLQ problem. Without knowing three system coefficient…

Optimization and Control · Mathematics 2022-09-30 Heng Zhang , Na Li

This paper proposes an effective low-rank alternating direction doubling algorithm (R-ADDA) for computing numerical low-rank solutions to large-scale sparse continuous-time algebraic Riccati matrix equations. The method is based on the…

Numerical Analysis · Mathematics 2024-04-23 Juan Zhang , Wenlu Xun

We propose a new algorithm for a broad class of periodic time-varying Stochastic Game-Theoretic Riccati Differential Equations arising in Zero-Sum Linear-Quadratic Stochastic Differential Games. The algorithm is constructed via dual-layer…

Numerical Analysis · Mathematics 2025-11-06 Yiyuan Wang

The linearly constrained matrix rank minimization problem is widely applicable in many fields such as control, signal processing and system identification. The tightest convex relaxation of this problem is the linearly constrained nuclear…

Optimization and Control · Mathematics 2009-05-12 Shiqian Ma , Donald Goldfarb , Lifeng Chen

In this paper, we investigate the mean-square stabilization for discrete-time stochastic systems that endure both multiple input delays and multiplicative control-dependent noises. For such multi-delay stochastic systems, we for the first…

Optimization and Control · Mathematics 2023-03-16 Cheng Tan , Zhengqiang Zhang , Haoting Sui , Wing Shing Wong

In this paper, we establish results fully addressing two open problems proposed recently by I. Ivanov, see Nonlinear Analysis 69 (2008) 4012--4024, with respect to the convergence of the accelerated Riccati iteration method for solving the…

Optimization and Control · Mathematics 2026-03-24 Prasanthan Rajasingam , Jianhong Xu

We review a family of algorithms for Lyapunov- and Riccati-type equations which are all related to each other by the idea of \emph{doubling}: they construct the iterate $Q_k = X_{2^k}$ of another naturally-arising fixed-point iteration…

Numerical Analysis · Mathematics 2020-05-19 Federico Poloni

In this paper, we reveal the intrinsic Toeplitz structure in the unique stabilizing solution for nonsymmetric algebraic Riccati equations by employing a shift-involved fixed-point iteration, and propose an RADI-type method for computing…

Numerical Analysis · Mathematics 2025-10-01 Zhen-Chen Guo , Xin Liang

In this paper, the discrete-time modified algebraic Riccati equation (MARE) is solved when the system model is completely unavailable. To achieve this, firstly a brand new iterative method based on the standard discrete-time algebraic…

Systems and Control · Electrical Eng. & Systems 2024-07-19 Fei Yan , Jie Gao , Tao Feng , Jianxing Liu

Fisher discriminant analysis (FDA) is a widely used method for classification and dimensionality reduction. When the number of predictor variables greatly exceeds the number of observations, one of the alternatives for conventional FDA is…

Machine Learning · Statistics 2018-11-30 Agniva Chowdhury , Jiasen Yang , Petros Drineas
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