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When we increase the dimensions, the number of near neighbors increases very rapidly. In general, the value is given by the kissing numbers. The result is that the number of ways for noise to make the receiver choose a neighbor (hence an error) grows as well. This is a fundamental limitation of block codes, and indeed all codes.
Off-by-one errors are common in using the C library because it is not consistent with respect to whether one needs to subtract 1 byte – functions like fgets() and strncpy will never write past the length given them (fgets() subtracts 1 itself, and only retrieves (length − 1) bytes), whereas others, like strncat will write past the length given them.
x erf x 1 − erf x; 0: 0: 1: 0.02: 0.022 564 575: 0.977 435 425: 0.04: 0.045 111 106: 0.954 888 894: 0.06: 0.067 621 594: 0.932 378 406: 0.08: 0.090 078 126: 0.909 ...
Often the only clue to the existence of logic errors is the production of wrong solutions, ... This example function in C to calculate the average of two numbers ...
In cryptography, learning with errors (LWE) is a mathematical problem that is widely used to create secure encryption algorithms. [1] It is based on the idea of representing secret information as a set of equations with errors. In other words, LWE is a way to hide the value of a secret by introducing noise to it. [2]
In some programming languages, an assignment statement returns a value, while in others it does not. In most expression-oriented programming languages (for example, C), the assignment statement returns the assigned value, allowing such idioms as x = y = a, in which the assignment statement y = a returns the value of a, which is then assigned to x.
For example, if we already know the values of F 41 and F 40, we can directly calculate the value of F 42. Some programming languages can automatically memoize the result of a function call with a particular set of arguments, in order to speed up call-by-name evaluation (this mechanism is referred to as call-by-need ).
In computing, a roundoff error, [1] also called rounding error, [2] is the difference between the result produced by a given algorithm using exact arithmetic and the result produced by the same algorithm using finite-precision, rounded arithmetic. [3]