A. J. Brandao, E. Fernandez-cara, P. Magalhaes, and M. A. Rojas-medar, Theoretical analysis and control results for the fitzhugh-nagumo equation, Electronic Journal of Differential Equations, vol.164, 2008.

E. Casas, C. Ryll, and F. Tröltzsch, Sparse optimal control of the schlögl and fitzhugh-nagumo systems, Computational Methods in Applied Mathematics, vol.13, issue.4, pp.415-442, 2013.

K. Kunisch and M. Wagner, Optimal control of the bidomain system (iii): Existence of minimizers and first-order optimality conditions, ESAIM: Mathematical Modelling and Numerical Analysis, vol.47, issue.4, pp.1077-1106, 2013.

N. Chamakuri, K. Kunisch, and G. Plank, Numerical solution for optimal control of the reaction-diffusion equations in cardiac electrophysiology, Computational Optimization and Applications, vol.49, issue.1, pp.149-178, 2011.

N. Chamakuri and K. Kunisch, Primal-dual active set strategy for large scale optimization of cardiac defibrillation, Applied Mathematics and Computation, vol.292, pp.178-193, 2017.

M. Bendahmane, N. Chamakuri, E. Comte, and B. Ainseba, A 3d boundary optimal control for the bidomain-bath system modeling the thoracic shock therapy for cardiac defibrillation, Journal of Mathematical Analysis and Applications, vol.437, issue.2, pp.972-998, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01261547

D. Ngoma, P. Vianney, Y. Bourgault, and H. Nkounkou, Parameter identification for a non-differentiable ionic model used in cardiac electrophysiology, Applied Mathematical Sciences, vol.9, issue.150, pp.7483-7507, 2015.

Y. Abidi, M. Bellassoued, M. Mahjoub, and N. Zemzemi, On the identification of multiple space dependent ionic parameters in cardiac electrophysiology modelling, Inverse Problems, vol.34, issue.3, p.35005, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01567714

Y. Abidi, M. Bellassoued, M. Mahjoub, and N. Zemzemi, Ionic parameters identification of an inverse problem of strongly coupled pdes system in cardiac electrophysiology using carleman estimates, Math. Model. Nat. Phenom, vol.14, issue.2, p.202, 2019.

H. Yang and A. Veneziani, Estimation of cardiac conductivities in ventricular tissue by a variational approach, Inverse Problems, vol.31, issue.11, p.115001, 2015.

C. E. Chávez, N. Zemzemi, Y. Coudière, F. Alonso-atienza, and D. Alvarez, Inverse problem of electrocardiography: Estimating the location of cardiac ischemia in a 3d realistic geometry, International Conference on Functional Imaging and Modeling of the Heart, pp.393-401, 2015.

B. F. Nielsen, M. Lysaker, and A. Tveito, On the use of the resting potential and level set methods for identifying ischemic heart disease: An inverse problem, Journal of computational physics, vol.220, issue.2, pp.772-790, 2007.

J. Bouyssier and N. Zemzemi, Parameters estimation approach for the mea/hipsc-cm asaays, Computing in Cardiology (CinC), pp.1-4, 2017.

A. L. Hodgkin and A. F. Huxley, A quantitative description of membrane current and its application to conduction and excitation in nerve, The Journal of Physiology, vol.117, issue.4, pp.500-544, 1952.

P. C. Franzone, L. F. Pavarino, and S. Scacchi, Mathematical Cardiac Electrophysiology, 2014.

C. H. Luo and Y. Rudy, A model of the ventricular cardiac action potential: Depolarization, repolarization, and their interaction, Circulation Research, vol.68, issue.6, pp.1501-1526, 1991.

G. W. Beeler and H. Reuter, Reconstruction of the action potential of ventricular myocardial fibres, The Journal of Physiology, vol.268, issue.1, pp.177-210, 1977.

M. Veneroni, Reaction-diffusion systems for the macroscopic bidomain model of the cardiac electric field, Nonlinear Analysis: Real World Applications, vol.10, pp.849-868, 2009.

M. A. Fernã¡ndez and N. Zemzemi, Decoupled time-marching schemes in computational cardiac electrophysiology and ecg numerical simulation, Mathematical biosciences, vol.226, issue.1, pp.58-75, 2010.