A theoretical result for processing signals that have unknown distributions and priors in white Gaussian noise

DOI10.1016/J.CSDA.2007.10.011zbMath1452.62109OpenAlexW2104174839MaRDI QIDQ1023651

Dominique Pastor

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.10.011

zbMATH Keywords

decisionestimationsignal processingthresholdingmultivariate normal distributionstatistical testbinary hypothesis testinglikelihood theory

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Detection theory in information and communication theory (94A13)

Related Items (2)

Detection threshold for non-parametric estimation ⋮ Editorial: Some recent trends in applied stochastic modeling and multidimensional data analysis

Uses Software

• WaveSpect0

Cites Work

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• Wavelet-based procedures for proteomic mass spectrometry data processing
• On rank tests for shift detection in time series
• Ideal spatial adaptation by wavelet shrinkage
• A sharp upper bound for the probability of error of the likelihood ratio test for detecting signals in white Gaussian noise
• Detection of stochastic processes
• Tests of Statistical Hypotheses Concerning Several Parameters When the Number of Observations is Large

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