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An asymptotic viscosity selection result for the regularized Newton dynamic

Boushra Abbas

Abstract

Let $Φ:\mathcal{H}\longrightarrow\mathbb{R\cup}\left\{ +\infty\right\} $ be a closed convex proper function on a real Hilbert space $\mathcal{H}$, and $\partialΦ:\mathcal{H}\rightrightarrows\mathcal{H}$ its subdifferential. For any control function $ε:\mathbb{R}_{+}\longrightarrow\mathbb{R}_{+}$ which tends to zero as $t$ goes to $+\infty$, and $λ$ a positive parameter, we study the asymptotic behavior of the trajectories of the regularized Newton dynamical system \begin{eqnarray*} & & \upsilon\left(t\right)\in\partialΦ\left(x\left(t\right)\right) & & λ\dot{x}\left(t\right)+\dot{\upsilon}\left(t\right)+\upsilon\left(t\right)+\varepsilon\left(t\right)x\left(t\right)=0. \end{eqnarray*} Assuming that $\varepsilon\left(t\right)$ tends to zero moderately as $t$ goes to $+\infty$, we show that the term $\varepsilon\left(\cdot\right)x\left(\cdot\right)$ asymptotically acts as a Tikhonov regularization, which forces the trajectories to converge to a particular equilibrium. Precisely, when $C=\textrm{argmin}Φ\neq\emptyset$, and $\varepsilon (\cdot)$ is a ``slow'' control, i.e., $\int_{0}^{+\infty}\varepsilon\left(t\right)dt=+\infty$, then each trajectory of the system converges weakly, as $t$ goes to $+\infty$, to the element of minimal norm of the closed convex set $C.$ When $Φ$ is a convex differentiable function whose gradient is Lipschitz continuous, we show that the strong convergence property is satisfied. Then we examine the effect of other types of regularizing methods.

An asymptotic viscosity selection result for the regularized Newton dynamic

Abstract

Let be a closed convex proper function on a real Hilbert space , and its subdifferential. For any control function which tends to zero as goes to , and a positive parameter, we study the asymptotic behavior of the trajectories of the regularized Newton dynamical system \begin{eqnarray*} & & \upsilon\left(t\right)\in\partialΦ\left(x\left(t\right)\right) & & λ\dot{x}\left(t\right)+\dot{\upsilon}\left(t\right)+\upsilon\left(t\right)+\varepsilon\left(t\right)x\left(t\right)=0. \end{eqnarray*} Assuming that tends to zero moderately as goes to , we show that the term asymptotically acts as a Tikhonov regularization, which forces the trajectories to converge to a particular equilibrium. Precisely, when , and is a ``slow'' control, i.e., , then each trajectory of the system converges weakly, as goes to , to the element of minimal norm of the closed convex set When is a convex differentiable function whose gradient is Lipschitz continuous, we show that the strong convergence property is satisfied. Then we examine the effect of other types of regularizing methods.

Paper Structure

This paper contains 11 sections, 7 theorems, 121 equations.

Key Result

Theorem 2.1

Suppose that $\Phi:\mathcal{H}\longrightarrow\mathbb{R}\cup\left\{ +\infty\right\}$ is a convex lower semicontinuous proper function, and $\lambda>0$ is a positive constant. Let $\epsilon:\mathbb{R}_{+}\longrightarrow\mathbb{R}_{+}$ be a nonnegative locally integrable function, and $\left(x_{0},\ups where $y\left(\cdot\right):\left[0,+\infty\right[\longrightarrow\mathcal{H}$ is the unique strong g

Theorems & Definitions (20)

  • Theorem 2.1
  • proof
  • Definition 3.1
  • Definition 3.2
  • Definition 3.3
  • Definition 3.4
  • Remark 3.1
  • Remark 3.2
  • Remark 3.3
  • Lemma 3.1
  • ...and 10 more