The extened Kalman filter (EKF) and unscented Kalman filter (UKF) have been successively applied in particle filter framework to generate proposal distributions, and shown significantly improving performance of the generic particle filter that uses transition prior, i.e., the system state transition prior distribution, as the proposal distribution. In this paper we propose to use the Gauss-Newton EKF/UKF to replace EKF/UKF for generating proposal distribution in a particle filter. The Gauss-Newton EKF/UKF that uses iterated measurement update can approximate the optimal proposal distribution more closer than EKF/UKF, especially in the case of significant nonlinearity in the measurement function. As a result, the Gauss-Newton EKF/UKF is able to generate and propagate the proposal distribution for each particle much better than EKF/UKF, thus further improving the performance of state estimation. Simulation results for a nonlinear/non-Gaussian time-series demonstrate the superior estimation accuracy of our method compared with state-of-the-art filters.

A novel pedestrian tracking scheme based on a particle filter is proposed, which adopts a skeleton model of a pedestrian for a state space model and distance transformed images for likelihood computation. The 6-stick skeleton model used in the proposed approach is very distinctive in representing a pedestrian simply but effectively. By the experiment using the real sequences provided by PETS, it is shown that the target pedestrian is tracked adequately by the proposed approach with a simple silhouette extraction method which consists of only background subtraction, even if the tracking target moves so complicatedly and is often so cluttered by other obstacles that the pedestrian can not be tracked by the conventional methods. Moreover, it is demonstrated that the proposed scheme can track the multiple targets in the complex case that their trajectories intersect.

Authors have been working in particle accelerator wake field analysis by using the Time Domain Boundary Element Method (TDBEM). A stable TDBEM scheme was presented and good agreements with conventional wake field analysis of the FDTD method were obtained. On the other hand, the TDBEM scheme still contains difficulty of initial value setting on interior region problems for infinitely long accelerator beam pipe. To avoid this initial value setting, we adopted a numerical model of beam pipes with finite length and wall thickness on open scattering problems. But the use of such finite beam pipe models causes another problem of unwanted scattering fields at the beam pipe edge, and leads to the involvement of interior resonant solutions. This paper presents a modified TDBEM scheme, Scattered-field Time Domain Boundary Element Method (S-TDBEM) to treat the infinitely long beam pipe on interior region problems. It is shown that the S-TDBEM is able to avoid the excitation of the edge scattering fields and the involvement of numerical instabilities caused by interior resonance, which occur in the conventional TDBEM.

The Multiple Access Interference (MAI) and the Multipath Fading (MPF) restrict the performance of Code-Division Multiple-Access (CDMA) systems. The Multiuser Detection (MUD) based on Particle Swarm Optimization algorithm (PSO) with Rake processing is proposed in this paper to overcome these obstacles, followed by full details of how to apply the Binary PSO MUD (BPSO-MUD) on a CDMA system. Simulations show that the BPSO-MUD has significantly better performance than the Conventional Detection (CD).

In order to reduce the traffic load and improve the system's lifetime, a cluster-based routing protocol has attracted more attention. In cluster-based sensor networks, energy can be conserved by combining redundant data from nearby sensors into cluster head nodes before forwarding the data to the destination. The lifespan of the whole network can also be expanded by the clustering of sensor nodes and through data aggregation. In this paper, we propose a cluster-based routing protocol which uses the location information of sensors to assist in network clustering. Our protocol partitions the entire network into several clusters by a particle swarm optimization (PSO) clustering algorithm. In each cluster, a cluster head is selected to deal with data aggregation or compression of nearby sensor nodes. For this clustering technique, the correct selection of the number of clusters is challenging and important. To cope with this issue, an energy dissipation model is used in our protocol to automatically estimate the optimal number of clusters. Several variations of PSO-clustering algorithm are proposed to improve the performance of our protocol. Simulation results show that the performance of our protocol is better than other protocols.

This paper addresses a speech recognition problem in non-stationary noise environments: the estimation of noise sequences. To solve this problem, we present a particle filter-based sequential noise estimation method for front-end processing of speech recognition in noise. In the proposed method, a noise sequence is estimated in three stages: a sequential importance sampling step, a residual resampling step, and finally a Markov chain Monte Carlo step with Metropolis-Hastings sampling. The estimated noise sequence is used in the MMSE-based clean speech estimation. We also introduce Polyak averaging and feedback into a state transition process for particle filtering. In the evaluation results, we observed that the proposed method improves speech recognition accuracy in the results of non-stationary noise environments a noise compensation method with stationary noise assumptions.

This paper describes a soft error hardened latch (SEH-Latch) scheme that has an error correction function in the fine process. The storage node of the latch is separated into three electrodes and a soft error on one node is collected by the other two nodes despite the large amount and long-lasting influx of radiation-induced charges. To achieve this, we designed two types of SEH-Latch circuits and a standard latch circuit using 130-nm 2-well, 3-well, and also 90-nm 2-well CMOS processes. The proposed circuit demonstrated immunity that was two orders higher through an irradiation test using alpha-particles, and immunity that was one order higher through neutron irradiation. We also demonstrated forward body bias control, which improves alpha-ray immunity by 26% for a standard latch and achieves 44 times improvement in the proposed latch.

This paper introduces a modified particle swarm optimizer (PSO) called the Multi-Species Particle Swarm Optimizer (MSPSO) for locating all the global minima of multi-modal functions. MSPSO extend the original PSO by dividing the particle swarm spatially into a multiple cluster called a species in a multi-dimensional search space. Each species explores a different area of the search space and tries to find out the global or local optima of that area. We test our MSPSO for several multi-modal functions with multiple global optima. Our MSPSO can successfully locate all the global optima of all the test functions, and in particular, can locate all 18 global optima of the two-dimensional Shubert function. We also examined how the performance of MSPSO depends on various algorithm parameters.

Image segmentation denotes a process by which an image is partitioned into non-intersecting regions and each region is homogeneous. Utilizing histogram information to aim at segmenting an image is a commonly used method for many applications. In this paper, we view the image segmentation as an optimization problem. We find a curve which gives the best fit to the given image histogram, and the parameters in the curve are determined by using the particle swarm optimization algorithm. The experimental results to confirm the proposed approach are also included.

Particles several tens of nanometers in size were aligned in the desired positions in a controlled manner by using capillary force interaction and suspension flow. Latex beads 40-nm in diameter were aligned linearly around a 10-µm-hole template fabricated by lithography. Further control of their position and separation was realized using colloidal gold nanoparticles by controlling the particle-substrate and particle-particle interactions using an optical near field generated on the edge of a Si wedge, in which the separation of the colloidal gold nanoparticles was controlled by the direction of polarization.

We investigated the initial stage of Zn dot growth using near-field optical chemical vapor deposition. The dependence of the rate of Zn dot deposition on dot size revealed that the deposition rate was maximal when the dot grew to a size equivalent to the probe apex diameter. Such observed size-dependent resonance was in good agreement with theoretical results for dipole-dipole coupling with a Forster field between the deposited Zn dot and the probe apex.

Magnetic immunoassays utilizing magnetic marker and high Tc superconducting quantum interference device (SQUID) have been performed. In this magnetic method, binding-reaction between an antigen and its antibody is detected by measuring the magnetic field from the magnetic marker. First, we discuss the magnetic property of the marker, and show that Fe3O4 particles with diameter of 25 nm can be used for remanence measurement. We also show a design of the SQUID for sensitive detection of the magnetic signal from the marker. Next, we developed a measurement system utilizing the SQUID and a reaction chamber with very low magnetic contamination. Finally, we conducted an experiment on the detection of the biological materials called IL8 and IgE. At present, a few atto-mol of IL8 and IgE has been detected, which shows the high sensitivity of the present method.

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the face search problem as an integer nonlinear optimization problem (INLP) and expands the basic particle swarm optimization (PSO) to handle it. PSO works with a population of particles, each representing a subwindow in an input image. The subwindows are evaluated by how well they match a NN based face filter. A face is indicated when the filter response of the best particle is above a given threshold. Experiments on a set of 42 test images show the effectiveness of the proposed approach. Moreover, the effect of PSO parameter settings on the search performance was investigated.

We propose a stochastic model for signals generated through the electron multiplying effect of detectors in charged particle beam equipments. This model is based on a stochastic variable characterized by a log-normal type distribution. The model is simple and can be used to represent a wide dynamic range of signals from pulse-like signals when the primary beam current is small to continuous signals when the primary beam current is large. For the model base reference a normalization of actual signal detectors is presented. This base reference yields the unique stochastic parameter used in our model. The proposed model better approximates the actual signals in the power spectrum distribution as compared to the filtered Poisson method presented elsewhere.

Metal nanostructure of organic/metal interface showing photocurrent multiplication phenomenon more than 105-fold was investigated. Au films deposited on organic films were revealed to be a gathering of nanoparticles and the multiplication rate can be tuned by the particle size. Spatial gaps formed between Au sphere and organic surface, which provide the hole accumulation sites (structural trap), was concluded to be indispensable for the photocurrent multiplication.

Lymph-node detection system using a high Tc SQUID and ultra-small particles was proposed. Pseudo lymph nodes containing small iron particles were made and the magnetic signal was measured. The SQUID signal was proportional to the weight of the iron in the fluid. At the distance of 20 mm, the detectable minimum weight of the iron was 40 µg. We demonstrated that the possibility of the application of the system to the human body.

We have fabricated a prototype of interface devices between SFQ and CMOS circuits using HTS quasi-particle injection devices. By the injection of quasi-particles, the bridge area becomes resistive and high voltage appears at the drain electrode. As a test of device operation, we applied the signal of a function generator to the gate electrode and observed that the device successfully repeated on/off operation. We also succeeded in explaining the device characteristics by considering the thermal effects.

We report the measurements on the ramp-edge type Josephson and quasiparticle tunnel junctions with the different interface angle geometry using high-Tc YBa2Cu3O7-y (YBCO) electrodes. The YBCO/I/Ag tunnel junctions with different crystal-interface boundary angles are fabricated for the investigation of zero bias conductance peak. The angle dependent zero bias conductance peak typical to a dx2-y2-wave superconductor is observable. For Josephson junctions, YBCO ramp-edge junctions with different ab-plane electrodes relatively rotated by 45are fabricated using a CeO2 seed-layer technique. The temperature dependence of the maximum Josephson current for YBCO/PBCO/YBCO junctions (PBCO: PrBa2Cu3O7-y) exhibits angle-dependent behavior, qualitatively different from the Ambegaokar-Baratoff prediction. Under microwave irradiation of 9 GHz, the Shapiro steps appear at integer and/or half integer multiples of the voltage satisfying Josephson voltage-frequency relation, whose behavior depends on the sample angle geometry. The results are reasonably interpreted by the dx2-y2-wave theory by taking the zero energy state into account.

Particulate media composed of very small particles were studied to determine high-density recording performance and thermal stability. Studied media included metal particulate media with mean particle length of 71, 102 and 148 nm, and Ba ferrite particulate media with mean diameter of 22, 28 and 50 nm. Using a loss-term simulation program, taking into account gap-loss, spacing-loss and particle length loss, the recording capability (D20 of 265 kFRPI for MP and 290 kFRPI for Ba ferrite media) was estimated. Thermal stability was evaluated from magnetization time decay measurements. It was found that MP media with large Ku values and 71 nm particles were satisfactorily stable, and the particle volume is still large enough in respect of thermal stability. However, 22-nm Ba ferrite media were less stable, primarily because of small Ku values and particle volume. It was also clarified that positive inter-particle interaction accelerates magnetization time decay, in the presence of a large reverse field.

A high Tc superconducting quantum interference device (SQUID) magnetometer system is developed for the application to biological immunoassay. In this application, magnetic nanoparticles are used as magnetic markers to perform immunoassay, i.e., to detect binding reaction between an antigen and its antibody. The antibody is labeled with γ-Fe2O3 nanoparticles, and the binding reaction can be magnetically detected by measuring the magnetic field from the nanoparticles. Design and set up of the system is described, and the sensitivity of the system is studied in terms of detectable number of the magnetic markers. At present, we can detect 4106 markers when the diameter of the marker is 50 nm. Total weight of the magnetic nanoparticles becomes 520 pg in this case. An experiment is also conducted to measure antigen-antibody reaction with the present system. It is shown that the sensitivity of the present system is 10 times better than that of the conventional method using an optical marker. A one order of magnitude improvement of sensitivity will be realized by the sophistication of the present system.