Bruce R. Musicus
Massachusetts Institute of Technology
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Bruce R. Musicus.
IEEE Transactions on Acoustics, Speech, and Signal Processing | 1985
Bruce R. Musicus
We derive a fast algorithm for calculating the Capon maximum likelihood method (MLM) power spectrum estimate when given uniformly spaced samples of the correlation function. This algorithm computes a weighted correlation of the predictor coefficients found by running Levinson recursion. The Fourier transform of the result gives the MLM spectrum. This approach also suggests an interesting new comparison between MLM and MEM.
Siam Journal on Scientific and Statistical Computing | 1987
C.-C. Jay Kuo; Bernard C. Levy; Bruce R. Musicus
A local relaxation method for solving linear elliptic PDEs with
IEEE Transactions on Signal Processing | 1993
Paul E. Beckmann; Bruce R. Musicus
O(N)
international conference on acoustics, speech, and signal processing | 1979
Bruce R. Musicus; Jae S. Lim
processors and
international conference on acoustics, speech, and signal processing | 1983
Bruce R. Musicus
O(\sqrt N )
IEEE Transactions on Signal Processing | 1991
Mordechai Segal; Ehud Weinstein; Bruce R. Musicus
computation time is proposed. We first examine the implementation of traditional relaxation algorithms for solving elliptic PDEs on mesh-connected processor arrays, which require
acm symposium on parallel algorithms and architectures | 1991
G. N. Srinivasa Prasanna; Bruce R. Musicus
O(N)
Algorithmica | 1996
G. N. Srinivasa Prasanna; Bruce R. Musicus
processors and
IEEE Transactions on Parallel and Distributed Systems | 1994
G. N. Srinivasa Prasanna; Anant Agarwal; Bruce R. Musicus
O(N)
international conference on acoustics, speech, and signal processing | 1986
Bruce R. Musicus; Allen Martin. Kabel
computation time. The disadvantage of these implementations is that the determination of the acceleration factors requires some global communication at each iteration. The high communication cost increases the computation time per iteration significantly. Therefore, a local relaxation scheme is proposed to achieve the acceleration effect with very little global communication in the loading stage. We use a Fourier analysis approach to analyze the local relaxation method and also show its convergence. The convergence rate of the local relaxation method is studied by computer simulation.