Title :
Regularized image reconstruction using SVD and a neural network method for matrix inversion
Author :
Steriti, Ronald J. ; Fiddy, Michael A.
Author_Institution :
Dept. of Electr. Eng., Massachusetts Univ., Lowell, MA, USA
fDate :
10/1/1993 12:00:00 AM
Abstract :
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
Keywords :
Hopfield neural nets; image reconstruction; inverse problems; matrix algebra; Hopfield neural network; SVD; energy minimization; image reconstruction; matrix inversion; regularisation technique; robust matrix inverse; singular value decomposition; Discrete Fourier transforms; Frequency estimation; Hopfield neural networks; Image reconstruction; Matrices; Matrix decomposition; Neural networks; Productivity; Robustness; Singular value decomposition;
Journal_Title :
Signal Processing, IEEE Transactions on
