
doi: 10.1007/bf02242373
LetA 1 andA 2 be floating point numbers represented in arbitrary base β and randomly chosen from a logarithmic distribution. Letr denote the round-off error $$r = fl(A_1 * A_2 ) - (A_1 * A_2 )$$ where * is floating point multiplication and wherefl(A 1*A 2) denotes the normalizedN digit computer result of forming (A 1*A 2). This paper analyzes the mean and variance of both the actual round-off error and the fraction round-off error. This analysis relies upon sharp order estimates for the digit by digit deviation of logarithmically distributed numbers from uniformly distributed numbers. This completely resolves open questions of Kaneko and Liu and of Tsao. Also included is a generalization to arbitrary base (from binary) of an important round-off theorem of Henrici.
Roundoff error, Algorithms in computer science
Roundoff error, Algorithms in computer science
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
