Conventional method for media defect recovery in a low-density parity-check (LDPC) coded magnetic recording channel is erasure decoding. In erasure decoding, read back signal in media defect region is erased and not used in channel detection or iterative decoding. In this paper, a new method based on full-response reequalization, in which media defect corrupted signal is first reequalized to full response then partially used in iterative decoding, is proposed. Simulation results show significant performance improvement over conventional erasure decoding in both non-precoded and precoded channels.
The aggregate conversion from the complex physical network topology to the simple virtual topology reduces not only load overhead, but also the parameter distortion of links and nodes during the aggregation process, thereby increasing the accuracy of routing. To this end, focusing on topology aggregation of multi-domain optical networks, a new topology aggregation algorithm (ML-S) was proposed. ML-S upgrades linear segment fitting algorithms to multiline fitting algorithms on stair generation. It finds mutation points of stair to increase the number of fitting line segments and makes use of less redundancy, thus obtaining a significant improvement in the description of topology information. In addition, ML-S integrates stair fitting algorithm and effectively alleviates the contradiction between the complexity and accuracy of topology information. It dynamically chooses an algorithm that is more accurate and less redundant according to the specific topology information of each domain. The simulation results show that, under different topological conditions, ML-S maintains a low level of underestimation distortion, overestimation distortion, and redundancy, achieving an improved balance between aggregation degree and accuracy.
Distributed protection relay value setting is widely applied in china. There is a graph chaos problem in protection relay model splicing process. Deeply study the characteristic of integrated relay splicing, combined with the substation voltage level, a substation locating method based on improved genetic algorithm is proposed. To enhance the graph splicing, a voltage level based method is applied. At last, a practical example is used to validate the effectiveness of the method.
At present, distributed integration setting calculation mode is widely used in power system. However, there are cross and overlap issues in protection relay model splicing process. Deeply researched in the characteristic of integrated relay splicing, according to power system network topology, an intelligent substation locating method based on the repulsion tension algorithm is applied in this paper. Finally, an example is used to verify the feasibility of the method.
Designing an excellent original topology not only improves the accuracy of routing, but also improves the restoring rate of failure. In this paper, we propose a new heuristic topology generation algorithm-GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption. The novelty lies in designing the two stages of genetic operation: The first stage is to pick the best population by means of the crossover, mutation, and selection operation; The second stage is to select an excellent individual from the best population. The simulation results show that, using the same number of nodes, GA-PODCC algorithm improves the balance of all the three optimization objectives, maintaining a low level of distortion in topology aggregation.
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