It is shown that the encoding/decoding problem for any asynchronous -user discrete memoryless multiple-access channel can be reduced to corresponding problems for at most 2 1 single-user discrete memoryless channels. This result, which extends a similar result for Gaussian channels, reduces the seemingly hard task of finding good multiple-access codes to the much better understood task of findi...

We present a model of roundoff error analysis that combines simplicity with predictive power. Though not considering all sources of roundoff within an algorithm, the model is related to a recursive roundoff error analysis and therefore is capable of correctly predicting stability or instability of an algorithm. By means of nontrivial examples, such as the componentwise backward stability analys...

In the last couple of years it has been realized that Gaussian elimination for sparse matrices arising from certain elliptic PDEs can be done in O(n log(1/ )) flops, where n is the number of unknowns and is a user-specified tolerance [Chandrasekaran and Gu]. The resulting solver will also be backward stable with an error of O( ). The techniques used to achieve this speedup has some commonality ...

Statistical models are simple mathematical rules derived from empirical data describing the association between an outcome and several explanatory variables. In a typical modeling situation statistical analysis often involves a large number of potential explanatory variables and frequently only partial subject-matter knowledge is available. Therefore, selecting the most suitable variables for a...

We show that for certain systems of linear equations with coefficient matrices of Hessenberg form it is possible to use Gaussian elimination to obtain an extrapolated version of the Gauss-Seidel iterative process where the iteration matrix has spectral radius zero. Computational aspects of the procedure are discussed.

The increasing interest in product networks (PNs) as a method of combining desirable properties of component networks, has prompted a need for the general study of the algorithmic issues related to this important class of interconnection networks. In this paper we present unified parallel algorithms for Gaussian elimination, with partial and complete pivoting, on product networks. A parallel al...

Classical target detection schemes are usually obtained by deriving the likelihood ratio under Gaussian hypothesis and replacing the unknown background parameters by their estimates. In most assumed to be Gaussian with zero mean [or with a known mean vector (MV)] and with an unknown covariance matrix (CM). When the MV is unknown, it has to be jointly estimated with the CM. In this paper, adapti...