Qinghua Wu

Circuit Design Based on Particle Swarm Optimization Algorithms

This work investigates the application of Particle Swarm Optimization (PSO) algorithms in the field of evolutionary electronics. PSO was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities. PSO achieves its optimum solution by starting from a group of random solution and then searching repeatedly. We propose the new means for designing electronic circuits and introduce the modified PSO algorithm. For the case studies this means has proved to be efficient, experiments show that we have better results.

Circuit Optimization Design Using Evolutionary Algorithms

During the space electronic system in carries out the exploratory mission in the deep space, it maybe faced with kinds of violent natural environment, to electric circuits performance, the volume, the weight and the stability proposed a higher request, the traditional circuit design method already more and more with difficulty satisfied this kind of request. The traditional circuit design method already more and more with difficulty satisfied this kind of request. But unifies the programmable component and the evolutionary algorithms hardware may the dynamic change hardwares structure adapt the adverse circumstance, resume the damage of the function, the adaptation for the duty change. After the optimization, obtains the circuit structure will often stem from our anticipation, this will be the altitude which the experience and the skillful institute hope to attain with difficulty. In view of the Xilinx Companys FPGA unique feature, proposed one kind of evolutionary algorithms which uses in the space electronic system circuit optimization design and through the experiment proved, the algorithm obtains the circuit structure to surpass the tradition circuit design method. This work investigates the application of genetic algorithms in the field of circuit optimization. For the case studies, this means has proved to be efficient and the experiment results show that the new means have got the better results.

Constrained Engineering Optimization Algorithm Based on Elite Selection

Many engineering optimization problems can be state as function optimization with constrained, intelligence optimization algorithm can solve these problems well. Particle Swarm Optimization (PSO) algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities. In this paper, aim at the disadvantages of standard Particle Swarm Optimization algorithm like being trapped easily into a local optimum, we improve the standard PSO and propose a new algorithm to solve the overcomes of the standard PSO. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Experiment results reveal that the proposed algorithm can find better solution when compared to other heuristic methods and is a powerful optimization algorithm for constrained engineering optimization problems.

Research of Space Electronic Circuit Optimization Design

During the space electronic system in carries out the exploratory mission in the deep space, it maybe faced with kinds of violent natural environment, to electric circuits performance, the volume, the weight and the stability proposed a higher request, the traditional circuit design method already more and more with difficulty satisfied this kind of request. The traditional circuit design method already more and more with difficulty satisfied this kind of request. But unifies the programmable component and the evolutionary algorithms hardware may the dynamic change hardwares structure adapt the adverse circumstance, resume the damage of the function, the adaptation for the duty change. In view of the Xilinx Companys FPGA unique feature, proposed one kind of evolutionary algorithms which uses in the space electronic system circuit optimization design and through the experiment proved, the algorithm obtains the circuit structure to surpass the tradition circuit design method.

Research of electronic circuit optimisation design algorithm

In this paper, we improved the traditional evolutionary algorithm and investigate the new algorithm in the field of evolutionary electronics. In the new algorithm, we use intergenerational elite mechanism instead of the best individual retention mechanism, in this mechanism, the population of the front generation mixed with the new population which generate through crossover and mutation operations, then select the optimum individuals according to a certain probability. This method can save the genetic diversity in the population evolution better. For the case studies, this means has proved to be more efficient and the experiment results show that the new means have got the better results.

Research of Image Matching Based on Evolutionary Algorithm

In image matching research, how to ensure that best match’s accuracy of the premise and a significant reduction in the amount of computing is the focus of concern by researchers. Search strategy to find the best match location of the image matching process to determine the amount of computing of image matching, in the existing image matching method are used to traverse search strategy, it is difficult to reduce the amount of computing. This is a common defect of the existing image matching algorithm. Traditional evolutionary algorithm trapped into the local minimum easily. Therefore, based on a simple evolutionary algorithm and combine the base ideology of orthogonal test then applied it to the population initialization, to prevent local convergence to form a new evolutionary algorithm. Compared the traditional evolutionary algorithm, the new algorithm enlarges the searching space and the complexity is not high. We use this new algorithm in image matching; from the results we reach the conclusion: in the optimization precision and the optimization speed, the new algorithm is efficiency for the image match problem.