Accession Number : ADA119103

Title :   Preprints Resulting from Work under SRO 106: Non-Gaussian Signal Processing.

Descriptive Note : Technical papers.

Corporate Author : TEXAS UNIV AT AUSTIN APPLIED RESEARCH LABS

Personal Author(s) : Brokett,Patrick L

PDF Url : ADA119103

Report Date : 02 Aug 1982

Pagination or Media Count : 140

Abstract : Contents: The Likelihood Ratio Detector for Non-Gaussian Infinitely Divisible and Linear Stochastic Processes; The Equivalence of Weak, Strong and Complete Convergence in L1 for Kernel Density Estimates; On the Inconsistency of Bayesian Non-Parametric Estimators in Competing Risks/Multiple Decrement Models; When Does the Beta-th Percentile Residual Life Function Determine the Distribution; Variational Sums and Generalized Linear Processes; Identifiability for Dependent Multiple Decrement/Competing Risk Models; The Underwriting Risk and Return Paradox Revisited; Density Estimates of Surface and Bottom Reverberation.

Descriptors :   *Gaussian noise, *Stochastic processes, *Estimates, Reports, Signal processing, Maximum likelihood estimation, Convergence, Weak convergence, Kernel functions, Density, Estimates, Bayes theorem, Variations, Linear systems, Risk, Reverberation, Bottom bounce

Subject Categories : Statistics and Probability
      Operations Research

Distribution Statement : APPROVED FOR PUBLIC RELEASE