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Note that the rows correspond to the condition actually being positive or negative (or classified as such by the gold standard), as indicated by the color-coding, and the associated statistics are prevalence-independent, while the columns correspond to the test being positive or negative, and the associated statistics are prevalence-dependent.
Research and literature on concurrency testing and concurrent testing typically focuses on testing software and systems that use concurrent computing.The purpose is, as with most software testing, to understand the behaviour and performance of a software system that uses concurrent computing, particularly assessing the stability of a system or application during normal activity.
e. In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit ), establishes that for any given degree of noise contamination of a communication channel, it is possible (in theory) to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel.
Low-density parity-check (LDPC) codes are a class of highly efficient linear block codes made from many single parity check (SPC) codes. They can provide performance very close to the channel capacity (the theoretical maximum) using an iterated soft-decision decoding approach, at linear time complexity in terms of their block length.
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Automation-induced complacency. The concept of automation bias is viewed as overlapping with automation-induced complacency, also known more simply as automation complacency. Like automation bias, it is a consequence of the misuse of automation and involves problems of attention. While automation bias involves a tendency to trust decision ...
Regression with known σ² η may occur when the source of the errors in x's is known and their variance can be calculated. This could include rounding errors, or errors introduced by the measuring device. When σ² η is known we can compute the reliability ratio as λ = ( σ² x − σ² η) / σ² x and reduce the problem to the previous case.
Propagation of uncertainty. In statistics, propagation of uncertainty (or propagation of error) is the effect of variables ' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement ...