There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fi...There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.展开更多
Accumulated low density parity check （LDPCA） codec is proposed for DISCOVER project in distributed video coding （DVC）, which offers flexible coding rate. Although it can use feedback channel to adapt the rate to t...Accumulated low density parity check （LDPCA） codec is proposed for DISCOVER project in distributed video coding （DVC）, which offers flexible coding rate. Although it can use feedback channel to adapt the rate to the correlation of the video, but in real applications, using feedback channel can not always be possible. To solve this problem, some researchers proposed estimating the code rate at the encoder but the performance was not very good. Based on their researches, this paper considers the impact of convergence rate for iteration on rate estimate, which can be calculated using its check matrix. As a pilot study, this paper pays attention to the regular LDPCA codec. At the same time, it considers the impact of deviation in the estimated crossover probability, which gives some constraints to rate estimate. In the experiment, the proposed algorithm can improve the rate-distortion performance by up to 1 dB-1.2 dB.展开更多
Multi-objective parameter adjustment plays an important role in improving the performance of the cognitive radio （CR） system. Current research focus on the genetic algorithm （GA） to achieve parameter optimization ...Multi-objective parameter adjustment plays an important role in improving the performance of the cognitive radio （CR） system. Current research focus on the genetic algorithm （GA） to achieve parameter optimization in CR, while general GA always fall into premature convergence. Thereafter, this paper proposed a linear scale transformation to the fitness of individual chromosome, which can reduce the impact of extraordinary individuals exiting in the early evolution iterations, and ensure competition between individuals in the latter evolution iterations. This paper also introduces an adaptive crossover and mutation probability algorithm into parameter adjustment, which can ensure the diversity and convergence of the population. Two applications are applied in the parameter adjustment of CR, one application prefers the bit error rate and another prefers the bandwidth. Simulation results show that the improved parameter adjustment algorithm can converge to the global optimal solution fast without falling into premature convergence.展开更多
基金Project(60574030) supported by the National Natural Science Foundation of ChinaKey Project(60634020) supported by the National Natural Science Foundation of China
文摘There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.
文摘Accumulated low density parity check （LDPCA） codec is proposed for DISCOVER project in distributed video coding （DVC）, which offers flexible coding rate. Although it can use feedback channel to adapt the rate to the correlation of the video, but in real applications, using feedback channel can not always be possible. To solve this problem, some researchers proposed estimating the code rate at the encoder but the performance was not very good. Based on their researches, this paper considers the impact of convergence rate for iteration on rate estimate, which can be calculated using its check matrix. As a pilot study, this paper pays attention to the regular LDPCA codec. At the same time, it considers the impact of deviation in the estimated crossover probability, which gives some constraints to rate estimate. In the experiment, the proposed algorithm can improve the rate-distortion performance by up to 1 dB-1.2 dB.
基金supported by the National Natural Science Foundation of China (61172073)National Key Special Program(2012ZX03003005)+1 种基金the State Key Laboratory of Rail Traffic Control and Safety (RCS2011ZT003)Beijing Jiaotong University and the Fundamental Research Funds for the Central Universities
文摘Multi-objective parameter adjustment plays an important role in improving the performance of the cognitive radio （CR） system. Current research focus on the genetic algorithm （GA） to achieve parameter optimization in CR, while general GA always fall into premature convergence. Thereafter, this paper proposed a linear scale transformation to the fitness of individual chromosome, which can reduce the impact of extraordinary individuals exiting in the early evolution iterations, and ensure competition between individuals in the latter evolution iterations. This paper also introduces an adaptive crossover and mutation probability algorithm into parameter adjustment, which can ensure the diversity and convergence of the population. Two applications are applied in the parameter adjustment of CR, one application prefers the bit error rate and another prefers the bandwidth. Simulation results show that the improved parameter adjustment algorithm can converge to the global optimal solution fast without falling into premature convergence.
