Advanced Materials Research Vols. 655-657

Abstract: This paper presents an advanced verification environment based on VMM verification platform architecture which is constructed based on an object oriented language named System Verilog. The portable, reusable and extensible verification environment, which has a hierarchical structure，randomized excitation and self-check mechanism, efficiently improves the adequacy and reliability of verification and validation efficiency. The environment was used to verify an EEPROM controller which generated the reading and writing timing signals to operate EEPROM. The AHB bus function model-VIP, that used in the environment, reduced the development cycle efficiently. Additionally, the function coverage collected in the test platform gave an intuitive evidence of the verification adequacy and reliability.

Abstract: In the paper, we research frequency difference lock of two lasers. In the optical fiber Brillouin sensor, two beams of laser frequency stability around 11G to achieve stimulated Brillouin scattering or heterodyne detection. Currently, we mainly through the optical delay to implement the locking of the frequency difference in the Brillouin sense. through the electric field amplify circuit to improve lock accuracy and improve the system program.

Abstract: In surface assessment, the reference line extracted using the profile filter are always distorted by freak characteristics of the scratches and peaks of the profile. In order to overcome this problem, the robust spline filter and the Gaussian regression filter were recommended by ISO standards. However, their different algorithms and different filtering characteristics lead to the different mean lines for the assessment of the same surface. A novel robust spline filter based on the M-estimate theory is developed, which possesses the same filtering characteristic as the Gaussian regression filter. It is available for use and transfer of the international standards, as well as the comparison of the surface assessment results.

Abstract: Perpendicularity error has great influence on the quality and performance of the geometrical products, and it is of great importance to guarantee the interchangeability. Particle swarm optimization (PSO) is an extraordinarily useful intelligent optimization algorithm with several advantages of fast convergence rate and easy realization for computer in the multidimensional space function optimization and dynamic target optimization. As a result, it is very accurate and is accordant with the requirement of minimum zone method (MZC) using PSO to associate the base plane of perpendicularity error.

Abstract: The feature extraction is a great important step for face recognition. When all features are extracted and selected for face recognition, it results in poor recognition rate because there are too many irrelevant, redundant and noisy features which also increase the time consumption. Therefore, a good feature selection method is necessary. This problem can be regarded as a combinatorial optimization solution. To overcome this problem, An improved kernel principal component analysis based on chaotic artificial fish school algorithm is proposed. The feature subspace of face pictures is obtained by standard kernel principal component analysis where a better feature subspace is selected by improved chaotic artificial fish school algorithm which based on couple chaotic maps increases the diversity of fish, has better global convergence ability and is not easy to fall into local optimum when facing with complex problems. The experimental results show that the proposed method has significantly improved the performance of conventional kernel principal component analysis.

Abstract: This paper introduces the asymmetric separator, which is a class of binary relation. They can separate and merge things by their properties. It illustrates the operation of asymmetric separator, the asymmetric separator nucleus of general binary relation and the asymmetric separators determined by set or function. Some asymmetric separator spaces constituted by asymmetric separators are studied.

Abstract: Bacterial Foraging Algorithm (BFA) has recently emerged as a very powerful technique for optimization,but it also confronts the problems of slow convergence and premature convergence. To overcome the drawbacks of BFA, This article merge the idea of particle swarm optimization algorithm with adaptive inertia weigh into the bacterial foraging to improve the speed and convergence capabilities of BFA, and according to this a bacterial foraging algorithm based on PSO(APSO-BFA) is presented. Simulation results on five systems of nonlinear equations show that the proposed algorithm is superior to the other two kinds of bacterial foraging algorithm

Abstract: Bacterial Foraging Optimization(BFA) algorithm has recently emerged as a very powerful technique for real parameter optimization,but the E.coli algorithm depends on random search directions which may lead to delay in reaching the global solution.The quantum-behaved particle swarm optimization (QPSO) algorithm may lead to possible entrapment in local minimum solutions. In order to overcome the delay in optimization and to further enhance the performance of BFA,a bacterial foraging algorithm based on QPSO(QPSO-BFA) is presented.The new algorithm is proposed to combines both algorithms’ advantages in order to get better optimization values. Simulation results on eight benchmark functions show that the proposed algorithm is superior to the BFA,QPSO and BF-PSO.