The measures of detection quality and corresponding probabilities of error are calculated according to (32).
We propose an iterative and self-adapting algorithm which estimates very low probabilities of error.
Note that the proposed method provides very low probabilities of error, mostly of order 10-7, even in the presence of stronger attacks.
The detection performances, in the form of probabilities of error, in some non-Gaussian noise are evaluated versus the matched filter (MF) and Volterra filter (VF) through numerical simulations.
The (b) part of the claim follows from the analysis presented in Section 5. Notice that the fact that the probabilities of error exponentially vanish with when the expected values of the corresponding random variables differ is a classical result of detection and estimation theory [11].
The ability to distinguish true sequence variants from sequencing errors is a fundamental challenge in the discovery of SNP variants and genotyping efforts; thus it is important to understand the types and probabilities of error in base calls [ 32].
