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  2. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    This rounding rule is biased because it always moves the result toward zero. Round-to-nearest : f l ( x ) {\displaystyle fl(x)} is set to the nearest floating-point number to x {\displaystyle x} . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used.

  3. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.

  4. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    This type of rounding, which is also named rounding to a logarithmic scale, is a variant of rounding to a specified power. Rounding on a logarithmic scale is accomplished by taking the log of the amount and doing normal rounding to the nearest value on the log scale. For example, resistors are supplied with preferred numbers on a logarithmic scale.

  5. Kahan summation algorithm - Wikipedia

    en.wikipedia.org/wiki/Kahan_summation_algorithm

    The exact result is 10005.85987, which rounds to 10005.9. With a plain summation, each incoming value would be aligned with sum, and many low-order digits would be lost (by truncation or rounding). The first result, after rounding, would be 10003.1. The second result would be 10005.81828 before rounding and 10005.8 after rounding. This is not ...

  6. Numerical stability - Wikipedia

    en.wikipedia.org/wiki/Numerical_stability

    On the other hand, in numerical algorithms for differential equations the concern is the growth of round-off errors and/or small fluctuations in initial data which might cause a large deviation of final answer from the exact solution. [citation needed]

  7. Quantization (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Quantization_(signal...

    Rounding and truncation are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding. Quantization also forms the core of essentially all lossy compression algorithms.

  8. Rule of 72: What it is and how to use it - AOL

    www.aol.com/finance/rule-72-184255797.html

    The answer is roughly the number of years it will take for your money to double. For example, if your investment earns 4 percent a year, it would take about 72 / 4 = 18 years to double. This rule ...

  9. Double-checked locking - Wikipedia

    en.wikipedia.org/wiki/Double-checked_locking

    In software engineering, double-checked locking (also known as "double-checked locking optimization" [1]) is a software design pattern used to reduce the overhead of acquiring a lock by testing the locking criterion (the "lock hint") before acquiring the lock. Locking occurs only if the locking criterion check indicates that locking is required.