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In mathematics and electronics engineering, a binary Golay code is a type of linear error-correcting code used in digital communications. The binary Golay code, along with the ternary Golay code , has a particularly deep and interesting connection to the theory of finite sporadic groups in mathematics. [ 1 ]
It is the first self-balancing binary search tree data structure to be invented. [ 3 ] AVL trees are often compared with red–black trees because both support the same set of operations and take O ( log n ) {\displaystyle {\text{O}}(\log n)} time for the basic operations.
Shannon–Fano codes are suboptimal in the sense that they do not always achieve the lowest possible expected codeword length, as Huffman coding does. [1] However, Shannon–Fano codes have an expected codeword length within 1 bit of optimal. Fano's method usually produces encoding with shorter expected lengths than Shannon's method.
Codeforces (Russian: Коудфорсес) is a website that hosts competitive programming contests. [1] It is maintained by a group of competitive programmers from ITMO University led by Mikhail Mirzayanov. [ 2 ]
Moreover, unlike a binary search tree, most of this space is being used to store data: even for billions of elements, the pointers in a full vEB tree number in the thousands. The implementation described above uses pointers and occupies a total space of O ( M ) = O (2 m ) , proportional to the size of the key universe.
It is the first code with an explicit construction to provably achieve the channel capacity for symmetric binary-input, discrete, memoryless channels (B-DMC) with polynomial dependence on the gap to capacity. [1] Polar codes were developed by Erdal Arikan, a professor of electrical engineering at Bilkent University.
In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.
Increased Code Size: Unrolling increases the number of instructions, leading to larger program binaries. Higher Storage Requirements: The expanded code takes up more memory, which can be problematic for microcontrollers or embedded systems with limited storage. Instruction Cache Pressure: The unrolled loop consumes more space in the instruction ...