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Turbo coding is an iterated soft-decoding scheme that combines two or more relatively simple convolutional codes and an interleaver to produce a block code that can perform to within a fraction of a decibel of the Shannon limit.
Reducing ε can be done at the cost of CPU time. Near-optimal erasure codes trade correction capabilities for computational complexity: practical algorithms can encode and decode with linear time complexity. Fountain codes (also known as rateless erasure codes) are notable examples of near-optimal erasure codes.
The analysis of errors computed using the global positioning system is important for understanding how GPS works, and for knowing what magnitude errors should be expected. The Global Positioning System makes corrections for receiver clock errors and other effects but there are still residual errors which are not corrected.
The forward–backward algorithm runs with time complexity () in space (), where is the length of the time sequence and is the number of symbols in the state alphabet. [1] The algorithm can also run in constant space with time complexity O ( S 2 T 2 ) {\displaystyle O(S^{2}T^{2})} by recomputing values at each step. [ 2 ]
This creates static tables at compile time and link time that relate ranges of the program counter to the program state with respect to exception handling. [22] Then, if an exception is thrown, the runtime system looks up the current instruction location in the tables and determines what handlers are in play and what needs to be done.
A snippet of Python code with keywords highlighted in bold yellow font. The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some ...
Reverse accumulation is more efficient than forward accumulation for functions f : R n → R m with n ≫ m as only m sweeps are necessary, compared to n sweeps for forward accumulation. Backpropagation of errors in multilayer perceptrons, a technique used in machine learning , is a special case of reverse accumulation.
Error-correcting codes are used in lower-layer communication such as cellular network, high-speed fiber-optic communication and Wi-Fi, [11] [12] as well as for reliable storage in media such as flash memory, hard disk and RAM. [13] Error-correcting codes are usually distinguished between convolutional codes and block codes: