One class of new reliability preserving reduction Wstone bridge reduction and a class of networks namely WST networks are presented. The networks is an extension to S P networks . Based on this ,we give a new linear time algorithm for computing K terminal reliability of this class networks, the complexity of algorithm is O(|E| 2).
From the point of view of the computability theory,the paper expounds mathematical background for public key cryptosystem including the relationship between the complexity of algorithm and problem,the length of key,and security of cryptogram.
By using the time scanning of the algorithmic complexity value C(n) and earthquake intensity factor value Mf the study on 12 moderate earthquakes occurred in Henan province and its neighboring region has been carried out.
This paper studies the computational complexity of this problem, and obtains the following results: For any given integer k, 2≤k≤∞. the (k,2) path chromatic number problem for graphs and the (k,3) path chromatic number problem for graphs with diameter 2 are NP-complete ;
The simulation results based on a simplified traffic model show that the proposed algorithm guarantees better performances of efficiency and fairness than conventional algorithms, without increasing the algorithm complexity.
The algorithm complexity is the cost of a particular algorithm.
Functions of binary trees and their applications in algorithm complexity analysis
We describe several systems in each of these areas, focusing both on progress within the field, and the costs, benefits and interactions among different problem and algorithm complexity limitations used in the surveyed work.
The algorithm complexity and the tradeoffs for implementation are extensively discussed.
The computational complexity of Algorithm A is of orderO(2ck), wherek denotes the length of the LFSR andc>amp;lt;1 depends on the input parameters of the attack, and Algorithm B is polynomial (in fact, even linear) in the lengthk of the LFSR.
A remark on complexity of Algorithm 1 is given below.
CPU overhead depends on the complexity of algorithm and data structure.
For the time complexity of algorithm MFTB, we have the following theorem.
In summary, the complexity of algorithm elim-bel is dominated by the time and space needed to process a bucket.