For any given problem with A(1),A(2),…,A(n-1),A(n),and M, the time complexity of the algorithm is O(n~~(log_2(M+1)+1))and the space complexity is O(n), where A(1),A(2),…,A(n-1),A(n),and M are all positive integers.
But because of the much information involved in timetabling, and the time-complexity to get the optimal solution of timetabling is the index magnitude of the scale of timetabling, so for the problem of timetabling of certain scale, the ones that were generally adopted are the algorithms that got the better solutions.
The results show that the LIF can eliminate memory-space-cluster and reduce time-complexity in the join operation and can smooth the bottleneck of the join operation in the relational database system, so that the RDBP can achieve better performance in the join operation.
By studying the structure of 16 dimension Barnes-Wall lattice and lattices resulting from binary linear block codes and quaternary linear block codes based on Construction A, decoding problem of the lattices can be transformed into the problem of finding the shortest path of trellises accordingly. The time complexities of the decoding algorithms are analyzed.
In this paper, author have introduced an algorithm computing minimum free energy of the RNA secondary structure to find the RNA secondary structure having minimum free energy. The time complexities of this algorithm is not more than O(n4).
It is shown how the behavior of a system with a sparse spectrum up to time T=(1-ρ)/14ε can be predicted on a quantum computer with the time complexity t=4/(1-ρ)ε1 plus the time of classical algorithm, where ρ is the fidelity.
We examine the conditions under which resources compositions with required properties exist and estimate asymptotic time complexity of the corresponding algorithms.
The time complexity of the algorithm is O(mn2 + m7/2).
Two approximation algorithms are suggested, and the bounds for the relative error and time complexity are obtained.
Based on these results, the testing algorithm polynomial-time complexity for legal firing sequence is proposed.
In the process, we develop a hierarchy of time-complexity classes based on the Ackermann function.
If the users are asynchronous, the optimum multiuser detector can be implemented by a Viterbi algorithm whose time-complexity is linear in the number of symbols transmitted by each user and exponential in the number of users.
In order to achieve a good time-complexity for such an algorithm employing the divide-and-conquer paradigm, it is necessary to find an ambitus quickly.
The total time-complexity of our algorithm for the Euclidean bottleneck matching problem isO(n2 +n1.5 log0.5n).
The polynomial time-complexity of linear programming had just been established.