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%ما هو (من)٪ 1 - تعريف
COMPLEXITY CLASS (LOGARITHMIC SPACE)
Logspace; Deterministic logspace; L (complexity theory); Logarithmic space; Log space; LOGSPACE; L (complexity class); LSPACE; L (class); DLOGSPACE
L (complexity)
In computational complexity theory, L (also known as LSPACE or DLOGSPACE) is the complexity class containing decision problems that can be solved by a deterministic Turing machine using a logarithmic amount of writable memory space., Definition 8.
Computational complexity
MEASURE OF THE AMOUNT OF RESOURCES NEEDED TO RUN AN ALGORITHM OR SOLVE A COMPUTATIONAL PROBLEM
Asymptotic complexity; Computational Complexity; Bit complexity; Context of computational complexity; Complexity of computation (bit); Computational complexities
In computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements.
complexity
PROFESSIONAL ESPORTS ORGANIZATION BASED IN THE UNITED STATES
Los Angeles Complexity; CompLexity Gaming; LA Complexity; Complexity LA; CompLexity; Team CompLexity; CoL.Black; CoL
<algorithm> The level in difficulty in solving mathematically
posed problems as measured by the time, number of steps or
arithmetic operations, or memory space required (called time
complexity, computational complexity, and space complexity,
respectively).
The interesting aspect is usually how complexity scales with
the size of the input (the "scalability"), where the size of
the input is described by some number N. Thus an algorithm
may have computational complexity O(N^2) (of the order of the
square of the size of the input), in which case if the input
doubles in size, the computation will take four times as many
steps. The ideal is a constant time algorithm (O(1)) or
failing that, O(N).
See also NP-complete.
(1994-10-20)
ويكيبيديا
L (complexity)
In computational complexity theory, L (also known as LSPACE or DLOGSPACE) is the complexity class containing decision problems that can be solved by a deterministic Turing machine using a logarithmic amount of writable memory space. Formally, the Turing machine has two tapes, one of which encodes the input and can only be read, whereas the other tape has logarithmic size but can be read as well as written. Logarithmic space is sufficient to hold a constant number of pointers into the input and a logarithmic number of boolean flags, and many basic logspace algorithms use the memory in this way.
