Kei Eguchi

Euclidean Particle Swarm Optimization

Particle swarm optimization (PSO) is a swarm intelligence algorithm, has been successfully applied to many engineering optimization problems and shown its high search speed in these applications. However, as the dimension and the number of local optima of optimization problems increase, PSO and most existing improved PSO algorithms such as, the standard particle swarm optimization (SPSO) and the Gaussian particle swarm optimization (GPSO), are easily trapped in local optima. In this paper we proposed a novel algorithm based on SPSO called Euclidean particle swarm optimization (EPSO) which has greatly improved the ability of escaping from local optima. To confirm the effectiveness of EPSO, we have employed five benchmark functions to examine it, and compared it with SPSO and GPSO. The experiments results showed that EPSO is significantly better than SPSO and GPSO, especially obvious in higher-dimension problems.

A ring type switched-capacitor (SC) programmable converter with DC or AC input/DC or AC output

We have already proposed a ring type switched-capacitor (SC) converter. This converter consists of capacitors which make a ring connection switches. In this paper, we propose programmable converter of DC-DC, DC-AC, AC-DC and AC-AC using a ring type SC converter. The SPICE simulations show that the power efficiency is more than 80%. This converter can provide to some combination of DC or AC input/DC or AC output.

Design of chaotic binary sequences with good statistical properties based on piecewise linear into maps

This paper shows design of chaotic binary sequences with good statistical properties based on one-dimensional piecewise linear maps. Such chaotic binary sequences are shown to be balanced and i.i.d. (independent and identically distributed). We also realize such sequences by an analog circuit using switched-current (SI) techniques. The statistical properties of the sequences generated by such an analog circuit are also investigated by SPICE simulations.

Clonal Selection Algorithm with Aging Operators for Protein Structure Prediction on AB Off-Lattice Model

Immune algorithms (IAs) are microscopic view of evolutionary algorithms (EAs) and applied in combinatorial optimization problems. This paper addresses to a clonal selection algorithm (CSA) that is one of the most representative IA and was applied into the protein structure prediction (PSP) on AB off-lattice model, in which the memory B cells of the CSA was innovated by employing different strategies: local search and global search in the phase of the mutation. And the CSA was further improved by adding aging operator to combat the premature convergence. However the pure aging operator didn’t achieve effective results and sometimes the optimum solution was eliminated. To resolve this problem, the current best solution was reserved by an antibody and it was not eliminated when its age reached its life span. In our experiments the improved algorithm was compared with the standard CSA and the pure aging CSA, which of the results demonstrated that the improved strategy with the memory B cells and long life aging was very effective to overcome premature convergence and to avoid trapped in the local-best solution, and it was also effective in keeping the diversity of the small size population.

Implementation of 3D SRAD Algorithm on CUDA

Speckle reducing an isotropic diffusion (SRAD) for three dimensional (3D) ultrasound images is an an isotropic diffusion approach for smoothing speckled imagery and is based on the conventional an isotropic diffusion and the traditional speckle reducing filter. The 3D SRAD has improved the quality of edge preservation and the smoothness of homogenous regions, but it requires much time to complete complex computation that affects its real-time application. To resolve this problem, one parallel 3D SRAD (3D pSRAD) was proposed on CUDA that is a general purpose parallel computing architecture and has solved many complex computational problems efficiently. In additional, a lot of experiments based on real images were employed to demonstrate the effectiveness and availability for the algorithm. The experimental results revealed a 60X parallel speedup over the original 3D SRAD.

Synthesis and analysis of a multiple-input parallel SC DC-DC converter

As compared with parallel converters employing buck converters or boost converters, the analysis of multiple-input parallel switched-capacitor (SC) DC-DC converters is not sufficient. In this paper, a multiple-input parallel DC-DC converter designed by using SC techniques is proposed for mobile back-lighting applications, and handy theoretical formulas are given concerning the power efficiency and equivalent circuit. The proposed parallel converter consists of two different kinds of converter blocks: 1. a 1.5× step-up SC DC-DC converter employing an input voltage from a lithium battery and 2. a novel step-up converter employing an input voltage from solar cells. The proposed converter can offer the output voltage for display back-lighting from solar energy, because the proposed step-up converter can achieve not only a large step-up conversion ratio but also a wide input range. Hence, the proposed converter will enable us to realize a long battery life, reduction of heat, and so on. Furthermore, derived theoretical formulas will be helpful to estimate circuit characteristics, because theoretical results agree well with SPICE simulation results. The validity of circuit design is confirmed by simulations and experiments.

Paralleling Euclidean Particle Swarm Optimization in CUDA

Euclidean Particle Swarm Optimization (EPSO) is a swarm intelligence algorithm, which has been successful applied to many engineering optimization problems and shown its high search speed in these applications. However, with the increase in the dimension of optimization problems and the number of local optima, the processing speed of the EPSO has become a bottleneck of applications as each particle of them has to calculate separately fitness. In this paper the EPSO has been parallelled in Compute Unified Device Architecture (CUDA) to solve the bottleneck. Five benchmark functions had been employed to examine the performance of the parallelled EPSO (pEPSO), and the experimental results shown that the average processing of calculating fitness had been accelerated to maximum 16.27 times the original algorithm.

Development of Switched-Capacitor bi-directional DC-AC converter for inductive and capacitive loads

This paper presents a research for Switched-Capacitor (SC) bi-directional DC-AC converter for inductive and capacitive loads. The proposed converter keeps high efficiency even if the phase of the load is changed widely, since the output energy returns to the input. The validity of the proposed converter is confirmed by SPICE simulations. The SPICE simulations showed that (1) the output voltage is kept a sinusoidal for the capacitive load and/or the inductive load, (2) the power conversion efficiency η is 93% or more regardless the phase θ of the load (−72≪θ ≪72) without output regulation, and (3) the efficiency η<inf>reg</inf> is 80% or more (−54≪θ ≪54) with regulation.

Paralleling Genetic Annealing Algorithm with OpenMP

In this paper, a parallel Genetic Annealing Algorithm (GAA) combining with simulated annealing algorithm and genetic algorithms was proposed, which was implemented using distributed computing model that employed OpenMP on four core computer. In this algorithm, several sub-populations replaced the original single population, and each sub-population evolved independently, and the current best individual was distributed into all the sub-populations. The algorithm overcame premature convergence, and found global optima efficiently in less time. And the experiment results shown that the performance had been significantly improved.

Design of an Educational Support System for Self-Learning

An educational support system for self-learning of a pupil is proposed in this paper. The features of the proposed system are that 1. appropriate questions which depend on the ability level of the pupil are provided by using a fuzzy scheme and 2. learning situation and weak points of the pupil are given by employing a principal component analysis (PCA). Therefore, different from conventional support systems, the proposed system enables the teacher to obtain analytical data for giving suitable advice about study. As one of the simplest examples, the proposed system for arithmetic training is realized by using Visual Basic. The experimental results show that the proposed system can provide appropriate questions depending on the ability level of pupil.