The objective of this paper is to evaluate the impacts of impulsive class-A noise, co-channel interference due to other piconet, Rician fading on the packet error rate (PER), and throughput performance in the Bluetooth scatternet. Simulation results illustrate the significant difference in performance between synchronous and asynchronous Bluetooth systems. The paper also provides the insights on how to design Bluetooth scatternet for minimal PER and maximum throughput performance.

Recently, neural networks (NNs) have been extensively applied to many signal processing problem due to their robust abilities to form complex decision regions. In particular, neural networks add flexibility to the design of equalizers for digital communication systems. Recurrent neural network (RNN) is a kind of neural network with one or more feedback loops, whereas self-organizing map (SOM) is characterized by the formation of a topographic map of the input patterns in which the spatial locations (i.e., coordinates) of the neurons in the lattice are indicative of intrinsic statistical features contained in the input patterns. In this paper, we propose a novel receiver structure by combining adaptive RNN equalizer with a SOM detector under serious ISI and nonlinear distortion in QAM system. According to the theoretical analysis and computer simulation results, the performance of the proposed scheme is shown to be quite effective in channel equalization under nonlinear distortion.

This paper proposes an idea for modeling aggregated TCP/IP traffic arriving at a bottleneck link by focusing on its scaling behavior. Here, the aggregated TCP/IP traffic means the IP packet traffic from many TCP connections sharing the bottleneck link. The model is constructed based on the outcomes of our previous works investigating how the TCP/IP networking mechanism affects the self-similar scaling behavior of the aggregated TCP/IP traffic in a LAN/WAN environment. The proposed traffic model has been examined from the perspective of application to network performance estimation. The examinations have shown that it models the scaling behavior and queueing behavior of actual traffic, though it neglects the interaction among TCP connections that compete with each other for the single bottleneck link bandwidth.

In this paper we treat a novel adaptation strength according to neighborhood ranking of self-organizing neural networks with the objective of avoiding the initial dependency of reference vectors, which is related to the strength in the neural-gas network suggested by Martinetz et al. The present approach exhibits the effectiveness in the average distortion compared to the conventional technique through numerical experiments. Furthermore the present approach is applied to image data and the validity in employing as an image coding system is examined.

This paper describes a QoS evaluation method for VoIP communications using a self-organizing neural network. Based on measurements in real environments, evaluation results confirmed that our method can effectively display total QoS level composed of several QoS-related factors such as PSQM+ and end-to-end delay.

Studies on artificial neural network have been conducted for a long time, and its contribution has been shown in many fields. However, the application of neural networks in the real world domain is still a challenge, since nature does not always provide the required satisfactory conditions. One example is the class size imbalanced condition in which one class is heavily under-represented compared to another class. This condition is often found in the real world domain and presents several difficulties for algorithms that assume the balanced condition of the classes. In this paper, we propose a method for solving problems posed by imbalanced training sets by applying the modified large-scale neural network "CombNET-II. " CombNET-II consists of two types of neural networks. The first type is a one-layer vector quantization neural network to turn the problem into a more balanced condition. The second type consists of several modules of three-layered multilayer perceptron trained by backpropagation for finer classification. CombNET-II combines the two types of neural networks to solve the problem effectively within a reasonable time. The performance is then evaluated by turning the model into a practical application for a fog forecasting problem. Fog forecasting is an imbalanced training sets problem, since the probability of fog appearance in the observation location is very low. Fog events should be predicted every 30 minutes based on the observation of meteorological conditions. Our experiments showed that CombNET-II could achieve a high prediction rate compared to the k-nearest neighbor classifier and the three-layered multilayer perceptron trained with BP. Part of this research was presented in the 1999 Fog Forecasting Contest sponsored by Neurocomputing Technical Group of IEICE, Japan, and CombNET-II achieved the highest accuracy among the participants.

This paper discusses self-similarity in cell dwell time of a mobile terminal, the discovery of which was described in our previous paper, and its effects on teletraffic of mobile communication networks. We have evaluated various teletraffic statistics, such as cell dwell time and channel occupancy time, of a mobile terminal based on measurements of motion for various types of vehicles. Those results show that cell dwell time follows a long-tailed log-normal distribution rather than the exponential distribution that has been used for modeling. Here, we first elaborate on self-similarity in cell dwell time of various vehicles. We then evaluate self-similarity in channel occupancy time. For future mobile multimedia communication systems employing a micro-cell configuration, it is anticipated that data communication will be the main form of communication and that call holding time will be long. For such cases, we have shown that channel occupancy time will be greatly affected by the cell dwell time of the mobile terminal, and that self-similarity, a characteristic that is not seen in conventional systems, will consequently appear. We have also found that hand-off frequently fails as self-similarity in cell dwell time of a mobile terminal becomes stronger.

Self-ordered mesoporous silicate films from organic-inorganic compound materials are successfully fabricated into the surface photo voltage (SPV) type gas sensor device as a gas adsorption insulator layer. These kinds of gas sensors device exhibit NO gas sensing property dependent on their mesoporous film structure. We are succeeded in indication about a possibility of mesoporous silicate film for the SPV type gas sensor application.

Most conventional studies on self-stabilization have been indifferent to the vulnerability under convergence. This paper investigates how mutual exclusion property can be achieved in self-stabilizing rings even for illegitimate configurations. We present a new method which uses a state with a large state space to detect faults. If some faults are detected, every process is reset and not given a privilege. Even if the reset values are different between processes, our protocol mimics the behavior of Dijkstra's unidirectional K-state protocol. Then we have a fast and safe mutual exclusion protocol. Simulation study also examines its performance.

The requirement to realize large-capacity, high-speed and guaranteed Quality of Service (QoS) communications in IP networks is a recent development. A technique to satisfy these requirements, Multi-Protocol Label Switching (MPLS) is the focus of this paper. In the future, it is expected that congestion and faults on a Label Switched Path (LSP) will seriously affect service contents because various applications are densely served in a large area. In MPLS, however, methods to solve these problems are not clear. Therefore, this study proposes a concrete traffic engineering method to avoid heavy congestion, and at the same time, endeavors to realize a fault-tolerant network by autonomous restoration, or self-healing.

Teletraffic characteristics of a mobile packet communication network, which supports mobile Internet, were quantitatively evaluated by using a terminal migration model in which the cell dwell time possesses self-similarity. I used a migration model in which the migration speed of the terminal is determined by the density of the dwell terminals in a cell (determined from measured vehicular mobility characteristics). The transmission rates per terminal in a cell were estimated as teletraffic on the mobile packet communication networks using this migration model. I found that when there is self-similarity in the terminal cell dwell time, communicating terminals may be concentrated in the cell and restricted for an indefinite period of time to using only a narrow bandwidth.

A mesh-connected processor array consists of many similar processing elements (PEs), which can be executed in both parallel and pipeline processing. For the implementation of an array of large numbers of processors, it is necessary to consider some fault tolerant issues to enhance the (fabrication-time) yield and the (run-time) reliability. In this paper, we introduce the 1(1/2)-track switch torus array by changing the connections in 1(1/2)-track switch mesh array, and we apply our approximate reconfiguration algorithm to the torus array. We describe the reconfiguration strategy for the 1(1/2)-track switch torus array and its realization using WSI, especially 3-dimensional realization. A hardware realization of the algorithm is proposed and simulation results about the array reliability are shown. These imply that a self-reconfigurable system with no host computer can be realized using our method, hence our method is effective in enhancing the run-time reliability as well as the fabrication-time yield of processor arrays.

We consider the problem of reconstructing architectural scenes from multiple photographs taken from arbitrary viewpoints. The original contribution is the use of a map as a source of geometric constraints to obtain in a fast and simple way a detailed model of a scene. We suppose that images are uncalibrated and have at least one planar structure as a faade for exploiting the planar homography induced between world plane and image to calculate a first estimation of the projection matrix. Estimations are improved by using correspondences between images and map. We show how these simple constraints can be used to calibrate the cameras and recover the projection matrices for each viewpoint. Finally, triangulation is used to recover 3D models of the scene and to visualise new viewpoints. Our approach needs minimal a priori information about the camera being used. A working system has been designed and implemented to allow the user to interactively build a model from uncalibrated images from arbitrary viewpoints and a simple map.

This paper proposes a linear algorithm for metric reconstruction from projective reconstruction. Metric reconstruction problem is equivalent to estimating the projective transformation matrix that converts projective reconstruction to Euclidean reconstruction. We build a quadratic form from dual absolute conic projection equation with respect to the elements of the transformation matrix. The matrix of quadratic form of rank 2 is then eigen-decomposed to produce a linear estimate. The algorithm is applied to three different sets of real data and the results show a feasibility of the algorithm. Additionally, our comparison of results of the linear algorithm to results of bundle adjustment, applied to sets of synthetic image data having Gaussian image noise, shows reasonable error ranges.

In this letter, we describe the conditions for measuring the nonlinear refractive index n2 when using the self-phase modulation-based cw dual-frequency method. We clarify the appropriate measurement conditions for dispersion-shifted and conventional single-mode fibers both numerically and experimentally. We also show experimentally that the evaluated n2 values for conventional single-mode fiber depend on the signal wavelength separation.

In this paper, a discrete-time convergence theorem for continuous-state Hopfield networks with self-interaction neurons is proposed. This theorem differs from the previous work by Wang in that the original updating rule is maintained while the network is still guaranteed to monotonically decrease to a stable state. The relationship between the parameters in a typical class of energy functions is also investigated, and consequently a "guided trial-and-error" technique is proposed to determine the parameter values. The third problem discussed in this paper is the post-processing of outputs, which turns out to be rather important even though it never attracts enough attention. The effectiveness of all the theorems and post-processing methods proposed in this paper is demonstrated by a large number of computer simulations on the assignment problem and the N-queen problem of different sizes.

This paper describes the adaptability of communication software through a biologically-inspired policy coordination. Many research efforts have developed adaptable systems that allow various users or applications to meet their specific requirements by configuring different design and optimization policies. Navigating through many policies manually, however, is tedious and error-prone. Developers face the significant manual and ad-hoc work of engineering an system. In contrast, we propose to provide autonomous adaptability in communication endsystem with OpenWebServer/iNexus, which is both a web server and an object-oriented framework to tailer various web services and applications. The OpenWebServer's modular architecture allows to abstract and maintain a wide range of aspects in a HTTP server, and reconfigure the system by adding, deleting, changing, or replacing their policies. iNexus is a tool for automated policy-based management of OpenWebServer. Its design is inspired by the natural immune system, particularly immune network, a truly autonomous decentralized system. iNexus inspects the current system condition of OpenWebServer periodically, measures the delivered quality of service, and selects suitable set of policies to reconfigure the system dynamically by relaxing constraints between them. The policy coordination process is performed through decentralized interactions among policies without a single point of control, as the natural immune system does. This paper discusses communication software can evolve continuously in the piecemeal way with biological concepts and mechanisms, adapting itself to ever-changing environment.

We have developed a novel self-alignment process using the surface tension of the liquid resin for assembly of electronic or optoelectronic devices. Though the liquid resins have a characteristics as low as one tenth of the surface tension of solder in general, restoring forces for self-alignment capability can be produced by making it constrained on the 3-dimensional pads on chip and substrate. In this paper, its principle and characteristics are described and the relationship between process parameters and joint geometry were examined. And the possibility of self-alignment process was verified by analytic numerical method and scaled-up experiment. A self-alignment accuracy was examined experimentally and show that it became less than 0.4 µm. It can provide a useful information on various parameters involved in joint geometry and optimal design guideline to generate the proper profiles.

This paper proposes an automatic dispersion equalization system using extracted clock power monitoring in order to facilitate the field installation of high-speed time-division multiplexed (TDM) systems over existing fiber cables. The proposed scheme adjusts the dispersion of a variable-dispersion equalizer so as to maximize the extracted clock power level. This scheme has a simple configuration, needs no communication channel between the transmitter and the receiver, and is sensitive to parameters such as initial chirping and fiber input power. The clock power dependence on the fiber dispersion is theoretically analyzed assuming that the return-to-zero (RZ) format is used and that pulse broadening is small compared to the bit duration. We show that the clock power is maximized when the dispersion-induced waveform distortion is minimized. Numerical simulations show that the proposed scheme is effective with the non-return-to-zero (NRZ) format and for the case that the optimum total dispersion deviates from zero due to initial and/or self-phase modulation (SPM)-induced chirping. The operation of the proposed automatic equalization system is experimentally confirmed in 20-Gbit/s transmission using both RZ and NRZ formats. Moreover, a 40-Gbit/s transmission experiment over 200 km of dispersion-shifted fiber (DSF) is successfully demonstrated using the proposed equalization scheme.

A signal suffers from nonlinear, linear, and additive distortion when transmitted through a channel. Linear equalizers are commonly used in receivers to compensate for linear channel distortion. As an alternative, novel equalizer structures utilizing neural computation have been developed for compensating for nonlinear channel distortion. In this paper, we propose a neural detector based on self-organizing map (SOM) in a 16 QAM system. The proposed scheme uses the SOM algorithm and symbol-by-symbol detector to form a neural detector, and it adapts well to the changing channel conditions, including nonlinear distortions because of the topology-preserving property of the SOM algorithm. According to the theoretical analysis and computer simulation results, the proposed scheme is shown to have better performance than traditional linear equalizer when facing with nonlinear distortion.