This paper deals with the L-1 analysis of linear sampled-data systems, by which we mean the computation of the L-infinity-induced norm of linear sampled-data systems. Two computation methods based on piecewise constant and piecewise linear approximations are provided through fast-lifting, by which the sampling interval [0, h) is divided into M subintervals with an equal width. Even though the central part of the method with the former approximation essentially coincides with a conventional method via fast-sample/fast-hold (FSFH) approximation after all, we show that both methods successfully lead to the upper and lower bounds of the L-infinity-induced norm, whose gap converges to 0 at the rate of 1/M in the former approximation and 1/M-2 in...
This article provides a new framework for the so-called L1 optimal control problem of sampled-data s...
This paper studies computation of ℓ2[0, h] induced norms of finite-dimensional linear systems. The p...
This paper is concerned with a new framework called the kernel approximation approach to the L1 opti...
This paper gives two methods for the L-1 analysis of sampled-data systems, by which we mean computin...
This paper provides a method for the L 1 analysis of sampled-data systems, by which we mean the comp...
This paper provides a discretization method for computing the induced norm from L₂ to L∞ in single-i...
This paper gives two methods for the L₁ analysis of sampled-data systems, by which we mean computing...
This paper develops a generalized framework for computing the -induced norm of sampled-data systems,...
This paper develops a new discretization method with piecewise linear approximation for the L-1 opti...
This paper develops a new discretization method with piecewise linear approximation for the L₁ optim...
This study deals with the L-1 analysis of stable finite-dimensional linear time-invariant (LTI) syst...
This paper considers linear time-invariant (LTI) sampled-data systems and studies their generalized ...
This study deals with the L₁ analysis of stable finite-dimensional linear time-invariant (LTI) syste...
This paper considers linear time-invariant (LTI) sampled-data systems and studies their generalized ...
This paper tackled the problem of characterizing the induced norm from L₂ to L∞ in single-input/sing...
This article provides a new framework for the so-called L1 optimal control problem of sampled-data s...
This paper studies computation of ℓ2[0, h] induced norms of finite-dimensional linear systems. The p...
This paper is concerned with a new framework called the kernel approximation approach to the L1 opti...
This paper gives two methods for the L-1 analysis of sampled-data systems, by which we mean computin...
This paper provides a method for the L 1 analysis of sampled-data systems, by which we mean the comp...
This paper provides a discretization method for computing the induced norm from L₂ to L∞ in single-i...
This paper gives two methods for the L₁ analysis of sampled-data systems, by which we mean computing...
This paper develops a generalized framework for computing the -induced norm of sampled-data systems,...
This paper develops a new discretization method with piecewise linear approximation for the L-1 opti...
This paper develops a new discretization method with piecewise linear approximation for the L₁ optim...
This study deals with the L-1 analysis of stable finite-dimensional linear time-invariant (LTI) syst...
This paper considers linear time-invariant (LTI) sampled-data systems and studies their generalized ...
This study deals with the L₁ analysis of stable finite-dimensional linear time-invariant (LTI) syste...
This paper considers linear time-invariant (LTI) sampled-data systems and studies their generalized ...
This paper tackled the problem of characterizing the induced norm from L₂ to L∞ in single-input/sing...
This article provides a new framework for the so-called L1 optimal control problem of sampled-data s...
This paper studies computation of ℓ2[0, h] induced norms of finite-dimensional linear systems. The p...
This paper is concerned with a new framework called the kernel approximation approach to the L1 opti...