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The location (in memory) of the code for handling an exception need not be located within (or even near) the region of memory where the rest of the function's code is stored. So if an exception is thrown then a performance hit – roughly comparable to a function call [ 24 ] – may occur if the necessary exception handling code needs to be ...
Lexicographic code; List decoding; Locally decodable code; Locally recoverable code; Locally testable code; Long code (mathematics) Longitudinal redundancy check; Low-density parity-check code; Luhn algorithm
A low code-rate close to zero implies a strong code that uses many redundant bits to achieve a good performance, while a large code-rate close to 1 implies a weak code. The redundant bits that protect the information have to be transferred using the same communication resources that they are trying to protect.
In computer programming, unreachable code is part of the source code of a program which can never be executed because there exists no control flow path to the code from the rest of the program. [ 1 ] Unreachable code is sometimes also called dead code , [ 2 ] [ 3 ] although dead code may also refer to code that is executed but has no effect on ...
Pages in category "Articles with example Python (programming language) code" The following 200 pages are in this category, out of approximately 201 total. This list may not reflect recent changes. (previous page)
The actual maximum code rate allowed depends on the error-correcting code used, and may be lower. This is because Shannon's proof was only of existential nature, and did not show how to construct codes that are both optimal and have efficient encoding and decoding algorithms.
Proof. We need to prove that if you add a burst of length to a codeword (i.e. to a polynomial that is divisible by ()), then the result is not going to be a codeword (i.e. the corresponding polynomial is not divisible by ()).
In machine learning, one-class classification (OCC), also known as unary classification or class-modelling, tries to identify objects of a specific class amongst all objects, by primarily learning from a training set containing only the objects of that class, [1] although there exist variants of one-class classifiers where counter-examples are used to further refine the classification boundary.