Computing the Eigen Decomposition of a Symmetric Matrix in Fixed-point Arithmetic
Since a number of signal processing algorithms requiring the EVD of a symmetric matrix are implemented on fixedpoint DSPs, there is considerable interest in matrix diagonalization algorithms that can be implemented in fixed-point arithmetic. We propose modifications to the Jacobi Cyclic Row algorithm that favor a fixed-point implementation. We then compare the eigenvalues and eigenvectors obtained from the Jacobi Algorithm implemented in fixed-point arithmetic to ones obtained from a floating point algorithm. For the matrices considered, we find that the EVD obtained from the fixedpoint implementation matches closely a floating-point implementation of the EVD decomposition. We also give an estimate of computational complexity of the fixed point algorithm.
View Entire Paper | Previous Page | White Papers Search
If you found this page useful, bookmark and share it on:
Embedded Star Newsletter
Don't have time to visit Embedded Star everyday? Then sign up for our free newsletter. We'll send you an email when we have something to share with you. Your email address will be kept confidential and we will not share, sell, or rent it to anyone. You can unsubscribe at any time by clicking a link in the email.
If you are familiar with RSS feeds, you can also sign up for our free blog feed. Our RSS feed is updated in real-time while our newsletter is updated daily.
