Genetic algorithm-based regularization parameter estimation for the inverse electrocardiography problem using multiple constraints
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Biomedical Engineering
Link
http://link.springer.com/content/pdf/10.1007/s11517-012-1005-6.pdf
Reference24 articles.
1. Ahmad GF, Brooks DH, MacLeod RS (1998) An admissible solution approach to inverse electrocardiography. Ann Biomed Eng 26(2):278–292
2. Aydin U, Dogrusoz YS (2011) A Kalman filter based approach to reduce the effects of geometric errors and the measurement noise in the inverse ECG problem. Med Biol Eng Comput 49(9):1003–1013
3. Berrier KL, Sorensen DC, Khoury DS (2004) Solving the inverse problem of electrocardiography using a Duncan and Horn formulation of the Kalman filter. IEEE Trans Biomed Eng 51(3):507–515
4. Brooks DH, Ahmad GF, MacLeod RS (1994) Multiply constrained inverse electrocardiography: combining temporal, multiple spatial, and iterative regularization. In: Proceedings of the 16th annual international conference of the IEEE EMBS
5. Brooks DH, Ahmad GF, MacLeod RS, Maratos GM (1999) Inverse electrocardiography by simultaneous imposition of multiple constraints. IEEE Trans Biomed Eng 46(1):3–18
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