Primal-dual active set strategy for large scale optimization of cardiac defibrillation

نویسندگان

  • Chamakuri Nagaiah
  • Karl Kunisch
چکیده

In this paper, the feasible study of the optimal control techniques for the cardiac defibrillation on the anatomical three spatial dimensional rabbit ventricle geometry in the presence of bilateral control constraints. The present work addresses the numerical treatment of multiscale and multidomain simulations of bidomain equations, the description of deriving optimality system, the applicability of primal-dual active set methods to treat the bilateral control constraints for solving such large scale optimization of cardiac defibrillation. The numerical results are demonstrated for the successful defibrillation study on 3D rabbit ventricle geometry by utilizing the less total currents, robustness of the optimization algorithm w.r.t to the variations in the model parameters, feasible study of the multiple smaller boundary control support and the numerical convergence of the optimization algorithm on the finer spatial grids. The parallel efficiency is demonstrated for the primal-dual active set optimization algorithm on such finer spatial grid.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization

We present a primal-dual active-set framework for solving large-scale convex quadratic optimization problems (QPs). In contrast to classical active-set methods, our framework allows for multiple simultaneous changes in the active-set estimate, which often leads to rapid identification of the optimal active-set regardless of the initial estimate. The iterates of our framework are the active-set ...

متن کامل

A Primal Dual Active Set with Continuation Algorithm for the \ell^0-Regularized Optimization Problem

We develop a primal dual active set with continuation algorithm for solving the l-regularized least-squares problem that frequently arises in compressed sensing. The algorithm couples the the primal dual active set method with a continuation strategy on the regularization parameter. At each inner iteration, it first identifies the active set from both primal and dual variables, and then updates...

متن کامل

A Primal Dual Active Set Algorithm for a Class of Nonconvex Sparsity Optimization

In this paper, we consider the problem of recovering a sparse vector from noisy measurement data. Traditionally, it is formulated as a penalized least-squares problem with an `1 penalty. Recent studies show that nonconvex penalties, e.g., `0 and bridge, allow more effective sparse recovery. We develop an algorithm of primal dual active set type for a class of nonconvex sparsity-promoting penalt...

متن کامل

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent

Over the past decades, Linear Programming (LP) has been widely used in differentareas and considered as one of the mature technologies in numerical optimization.However, the complexity offered by state-of-the-art algorithms (i.e. interior-pointmethod and primal, dual simplex methods) is still unsatisfactory for problems inmachine learning with huge number of variables and constr...

متن کامل

Primal-dual active set methods for Allen-Cahn variational inequalities

This thesis aims to introduce and analyse a primal-dual active set strategy for solving Allen-Cahn variational inequalities. We consider the standard Allen-Cahn equation with non-local constraints and a vector-valued Allen-Cahn equation with and without non-local constraints. Existence and uniqueness results are derived in a formulation involving Lagrange multipliers for local and non-local con...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Applied Mathematics and Computation

دوره 292  شماره 

صفحات  -

تاریخ انتشار 2017