errors tend to have higher rates of

false rejection than specifications using clustered standard errors and those using permutation tests for inference.

However, a single repeat 1:2s QC rule has recently been shown to have good power characteristics with a low

false rejection rate.

Users' security confidence is low due to the technology's non- optimized false acceptance rate (FAR) and

false rejection rate (FRR) rates.

In these environments, variables can potentially arise that create false acceptance or

false rejection situations which in turn can lead to unnecessary rework, increased cost, and the passing of faulty products.

The new fingerprint algorithm offers even higher reliability than the previous version: at the same False Acceptance Rate (FAR) level, the

False Rejection Rate (FRR) is up to three times smaller.

However, there are also

false rejection rates (FRR).

Performance characteristics of rules for internal quality control: probabilities for

false rejection and error detection.

The table includes single rules with control limits from 2s to 6s, multirole combinations for Ns of 2 and 4, multirole combinations for Ns of 3 and 6, single rules with fixed probabilities for

false rejection of 0.

These rules can be selected to give a high probability of error detection while maintaining low probabilities of

false rejection.

In NIST's modeling of a 2,000 enrollee identification for access control (where the time for template creation and matching were both considered), the L-1 iris technology showed the lowest

false rejection rate and the fastest composite match time of all five of the most accurate vendors.

5 SDK for fingerprint identification includes significant enhancements over the previous version in terms of recognition reliability, with a 20% decrease in the

false rejection rate (FRR) when set at the same false acceptance rate (FAR).

This results in high-precision certification, evidenced by a Hitachi-proven

false rejection rate of no more than 0.