We propose an algorithm which for any real number r, any k × l matrix M and any k-vector y, finds the l-vector x which minimizes ∥x∥2 - r2∥Mx - y∥2, i.e. it finds the "regularized" solution to the e...
A new iterative method is proposed for finding the optimal Bayesian estimate of an unknown image from its projection data (experimentally obtained integrals of its grayness over thin strips). Convergence of the method...
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