Regularized image reconstruction using SVD and a neural network method for matrix inversion
Ronald J. Steriti, Michael A. Fiddy · IEEE Transactions on Signal Processing · 1993
Two methods of matrix inversion are compared for use in an image reconstruction algorithm. The first is based on energy minimization using a Hopfield neural network. This is compared with the inverse obtained using singular value decomposition (SVD). It is shown for a practical example that the neural network provides a more useful and robust matrix inverse.>