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  2. Truncation - Wikipedia

    en.wikipedia.org/wiki/Truncation

    Truncation of positive real numbers can be done using the floor function. Given a number x ∈ R + {\displaystyle x\in \mathbb {R} _{+}} to be truncated and n ∈ N 0 {\displaystyle n\in \mathbb {N} _{0}} , the number of elements to be kept behind the decimal point, the truncated value of x is

  3. Unit in the last place - Wikipedia

    en.wikipedia.org/wiki/Unit_in_the_last_place

    In computer science and numerical analysis, unit in the last place or unit of least precision (ulp) is the spacing between two consecutive floating-point numbers, i.e., the value the least significant digit (rightmost digit) represents if it is 1. It is used as a measure of accuracy in numeric calculations. [1]

  4. Methods of computing square roots - Wikipedia

    en.wikipedia.org/wiki/Methods_of_computing...

    A method analogous to piece-wise linear approximation but using only arithmetic instead of algebraic equations, uses the multiplication tables in reverse: the square root of a number between 1 and 100 is between 1 and 10, so if we know 25 is a perfect square (5 × 5), and 36 is a perfect square (6 × 6), then the square root of a number greater than or equal to 25 but less than 36, begins with ...

  5. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    When using approximation equations or algorithms, especially when using finitely many digits to represent real numbers (which in theory have infinitely many digits), one of the goals of numerical analysis is to estimate computation errors. [5] Computation errors, also called numerical errors, include both truncation errors and roundoff errors.

  6. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    The problem was caused by the index being recalculated thousands of times daily, and always being truncated (rounded down) to 3 decimal places, in such a way that the rounding errors accumulated. Recalculating the index for the same period using rounding to the nearest thousandth rather than truncation corrected the index value from 524.811 up ...

  7. Computer number format - Wikipedia

    en.wikipedia.org/wiki/Computer_number_format

    which means "1.1030402 times 1 followed by 5 zeroes". We have a certain numeric value (1.1030402) known as a "significand", multiplied by a power of 10 (E5, meaning 10 5 or 100,000), known as an "exponent". If we have a negative exponent, that means the number is multiplied by a 1 that many places to the right of the decimal point. For example:

  8. Mathematical constant - Wikipedia

    en.wikipedia.org/wiki/Mathematical_constant

    Its numerical value truncated to 50 decimal places is: 1.41421 35623 73095 04880 16887 24209 69807 85696 71875 37694... (sequence A002193 in the OEIS). Alternatively, the quick approximation 99/70 (≈ 1.41429) for the square root of two was frequently used before the common use of electronic calculators and computers.

  9. ITP method - Wikipedia

    en.wikipedia.org/wiki/ITP_Method

    In numerical analysis, the ITP method, short for Interpolate Truncate and Project, is the first root-finding algorithm that achieves the superlinear convergence of the secant method [1] while retaining the optimal [2] worst-case performance of the bisection method. [3]