APA引文

Shaw, C. B., Prakash, J., Pramanik, M., Yalavarthy, P. K., & Engineering, S. o. C. a. B. (2014). Least squares QR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography.

Chicago Style Citation

Shaw, Calvin B., Jaya Prakash, Manojit Pramanik, Phaneendra K. Yalavarthy, and School of Chemical and Biomedical Engineering. Least Squares QR-based Decomposition Provides an Efficient Way of Computing Optimal Regularization Parameter in Photoacoustic Tomography. 2014.

MLA引文

Shaw, Calvin B., et al. Least Squares QR-based Decomposition Provides an Efficient Way of Computing Optimal Regularization Parameter in Photoacoustic Tomography. 2014.