In this paper, we describe a frame synchronization method for bi-orthogonal modulation systems. In bi-orthogonal modulation systems, several bi-orthogonal sequences are used for data transmission. Frame synchronization in bi-orthogonal modulation systems is difficult because transmitted sequences can change every frame. In the proposed method, each bi-orthogonal sequence consists of two different inner sequences. Each bi-orthogonal sequence has the same arrangement of two different inner sequences. A receiver can track the frame timing by observing the arrangement of inner sequences. In this paper, we analyze the bit error rate performance that takes into account the tracking performance of a system we developed based on our method. The spectral efficiency of the proposed system in code division multiple access (CDMA) systems is also investigated. As a result, we found that the proposed system is effective in synchronous CDMA systems.

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 proposes a vector quantization scheme which makes it possible to consider the dynamics of input vectors. In the proposed scheme, a linear transformation is applied to the consecutive input vectors and the resulting vector is quantized with a distortion measure defined by the statistics. At the decoder side, the output vector sequence is determined using the statistics associated with the transmitted indices in such a way that a likelihood is maximized. To solve the maximization problem, a computationally efficient algorithm is derived. The performance of the proposed method is evaluated in LSP parameter quantization. It is found that the LSP trajectories and the corresponding spectra change quite smoothly in the proposed method. It is also shown that the use of the proposed method results in a significant improvement of subjective quality.

Simulation based education and training, especially wargame simulations, are being used widely in the field of defense modeling and in simulation communities. In order to efficiently train students and trainees, the wargame simulations must have both high performance and high fidelity. In this paper, we discuss design and implementation issues for a prototype of a parallel and distributed wargame simulation system. This wargame simulation system is based on High Level Architecture (HLA) and employs some optimization to achieve both high performance and high fidelity in the simulation system. The results show that the proposed optimization method is effective when optimization is applied to 93.5% or less of the moving objects (PFs) within the range of detection (RofD) of both the red and blue teams. Specifically, when each team has 1000 PFs we found that if the percentage of PFs within RofD is less than 50% for both teams, our method is over two times better than for the situation where there is no optimization.

This document analyzes the characteristics of Waiting Time Jitter (WTJ) generated in High-bit-rate Digital Subscriber Lines (HDSL) systems transmitting non-uniform frames. It also derives the Fourier transform of the above WTJ.

The effect of Unbalanced-Magnetic-Pull (UMP) on vibration and run-outs has become stringent in the design for high performance HDD spindle motors. In this paper, reducing the UMP and also minimizing its variability for an 8-pole 9-slot spindle motor to achieve robustness in the performance is described and illustrated using novel robust design methods. A screening experiment identifies the key design parameters. Using Design of experiment (DOE) and Analysis of Variance (ANOVA), the parameter design reduces the amplitude of UMP and minimizes its variability by product parameter optimization. The tolerance design improves the quality by tightening tolerances on product or process parameters to reduce the performance variation. The optimal design process includes considerations of manufacturing and process noises, such as manufacturing tolerances for the slot opening and variation of the rotor magnet magnetization distribution due to the magnetization fixture and process. The optimal design procedure is briefly introduced and the results are presented.

This paper presents a fast inversion method for electromagnetic imaging of cylindrical dielectric objects with the optimal regularization parameter used in the Levenberg-Marquardt method. A novel procedure for choosing the optimal regularization parameter is proposed. The method of moments with pulse-basis functions and point matching is applied to discretize the equations for the scattered electric field and the total electric field inside the object. Then the inverse scattering problem is reduced to solving the matrix equation for the unknown expansion coefficients of a contrast function, which is represented as a function of the relative permittivity of the object. The matrix equation may be solved in the least-squares sense with the Levenberg-Marquardt method. Thus the contrast function can be reconstructed by the minimization of a functional, which is expressed as the sum of a standard error term on the scattered electric field and an additional regularization term. While a regularization parameter is usually chosen according to the generalized cross-validation (GCV) method, the optimal one is now determined by minimizing the absolute value of the radius of curvature of the GCV function. This scheme is quite different from the GCV method. Numerical results are presented for a circular cylinder and a stratified circular cylinder consisting of two concentric homogeneous layers. The convergence behaviors of the proposed method and the GCV method are compared with each other. It is confirmed from the numerical results that the proposed method provides successful reconstructions with the property of much faster convergence than the conventional GCV method.

Current-voltage characteristics of Cr-doped hydrogenated amorphous silicon-V (Cr/p+a-Si:H/V) analogue memory switching devices have been measured over a wide range of device resistance from several kilo-ohms to several hundred kilo-ohms, and over a temperature range from 13 K to 300 K. Both the bias and temperature dependence of the conductance show similar characteristics to that of metal-insulator heterogeneous materials (i.e. discontinuous or granular metallic films), which are analysed in terms of activated tunnelling mechanism. A modified filamentary structure for the Cr/p+a-Si:H/V switching devices is proposed. The influence of embedded metallic particles on memory switching is analysed and discussed.

In this paper we show that the neuron filter is effective for relaxing the coefficient sensitiveness of the Hopfield neural network for combinatorial optimization problems. Since the parameters in motion equation have a significant influence on the performance of the neural network, many studies have been carried out to support determining the value of the parameters. However, not a few researchers have determined the value of the parameters experimentally yet. We show that the use of the neuron filter is effective for the parameter tuning, particularly for determining their values experimentally through simulations.

Recently, the Guaranteed Frame Rate (GFR) service was proposed as a new service category of ATM to support non-realtime data applications and to provide the minimum rate guarantee. To keep the simplicity of GFR as much as possible and overcome defects of FIFO-based mechanisms, we propose a FIFO-based algorithm extending DFBA one to improve the fairness and provide the minimum rate guarantee for a wider range of Minimum Cell Rate (MCR). The key idea is controlling the number of CLP1 cells which are occupying more buffer space than the fair share even when the queue length is below Low Buffer Occupancy (LBO).

In the past, a number of scheduling algorithms that approximate GPS, such as WFQ, have been proposed and have received much attention. This class of algorithms provides per-flow QoS guarantees in terms of the bounded delay and minimum bandwidth guarantee. However, with O(log N) computational cost for each new arrival scheduling, where N is the number of backlogged flows, these algorithms are expensive to implement (e.g., in terms of scalability). Moreover, none of them addresses the issues of delay distribution and jitter. In this paper, we propose a new traffic scheduling discipline called Jitter Control Frame-based Queueing (JCFQ) that provides an upper bound for delay jitter in the case of rate-controlled connections, such as packet video streams and IP telephony, while guaranteeing bounded delay and worst-case fair weighted fairness, such as in the WF2Q algorithm, but with O(1) complexity in selecting the next packet to serve, assuming that the number of flows is fixed. Three different algorithms for slot or service order assignment between flows are proposed: Earliest Jitter Deadline First (EJDF), Rate Monotonic (RM) and Maximum Jitter First (MJF). In these algorithms, delay jitter is formulated into the virtual finish time calculation. We compare the fairness, delay and jitter performance of the JCFQ with that of the MJF algorithm with WF2Q via simulation. The results show that with proper choice of the slot size, JCFQ can achieve better flow isolation in delay distribution than can WF2Q.

This paper provides a new robust guaranteed cost controller design method for discrete parameter uncertain time delay systems. The result shows much tighter bound of guaranteed cost than that of existing paper. In order to get the optimal (minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) technique. Also, the parameter uncertain systems with time delays in both state and control input are considered.

New equivalent characterizations are derived for Schur stability property of real polynomials. They involve a single scalar parameter, which can be regarded as a freedom incorporated in the given polynomials so long as the stability is concerned. Possible applications of the expressions are suggested to the latest results for stability robustness analysis in parameter space. Further, an extension of the characterizations is made to the matrix case, yielding one-parameter expressions of Schur matrices.

We propose a method for compensating distortion of image by calibrating intrinsic camera parameters by image registration which does not need point-to-point correspondence. The proposed method divides the registration between a calibration pattern and a distorted image observed by a camera into two steps. The first step is the straightforward registration from the pattern in order to correct the displacement due to projection. The second step is the backward registration from the observed image for compensating the distortion of the image. Both of the steps use Gauss-Newton method, a nonlinear optimization technique, to minimize residuals of intensities so that the pattern and the observed image become the same. Experimental results show the usefulness of the proposed method. Finally we discuss the convergence of the proposed method which consists of the two registration steps.

This letter focuses on the design of a unified estimator for scheduled control in nonlinear systems with unknown parameter. An estimation law with a finite convergence time is formulated to compute the unknown scheduling parameter that drives a scheduled controller. This estimator can also be extended to the types of scheduled controllers addressed in the literature.

In this paper, we propose an adaptive video frame rate control method, called AFCON, that video encoders use in conjunction with explicit rate based congestion control in the network. First, an encoder buffer constraint which guarantees the end-to-end delay of video frames is derived under the assumption of bounded network transmission delay for every frame data. AFCON is based on the constraint and consists of future channel rate prediction, frame discarding, and frame skipping. Recursive Least-Squares (RLS) is used to predict the low-frequency component of the channel rate. Frame discarding prevents the delay violation of frames due to the prediction error of the channel rate. Frame skipping adapts the encoder output rate to the channel rate while avoiding abrupt quality degradation during the congestion period. From the simulation results, it is shown that AFCON can adapt to the time-varying rate channel with less degradation in temporal resolution and in PSNR performance compared to the conventional approach.

Network dimensioning is an important issue to provide stable and QoS-rich communication services. A reliable estimation of bandwidths of links between the end-to-end path is a first step towards the network dimensioning. Pathchar is one of such tools for the bandwidth estimation for every link between two end hosts. However, pathchar still has several problems. If unexpectedly large errors are included or if route alternation is present during the measurement, the obtained estimation is much far from the correct one. We investigate the method to eliminate those errors in estimating the bandwidth. To increase the reliability on the estimation, the confidence interval for the estimated bandwidth is important. For this purpose, two approaches, parametric and nonparametric approaches, are investigated to add the confidence intervals. Another important issue is the method for controlling the measurement period to eliminate the measurement overheads. In this paper, we propose a measurement method to adaptively control the number of measurement data sets. Through experimental results, we show that our statistical approaches can provide the robust estimation regardless of the network conditions.

Various shadows are one of main factors that cause errors in vision based vehicle detection. In this paper, two simple methods, land mark based method and BS & Edge method, are proposed for vehicle detection and shadow rejection. In the experiments, the accuracy of vehicle detection is higher than 98%, during which the shadows arisen from roadside buildings grew considerably. Based on these two methods, vehicle counting, tracking, classification, and speed estimation are achieved so that real-time traffic parameters concerning traffic flow can be extracted to describe the load of each lane.

We present a new family of algorithms that solve the bias problem in the equation-error based adaptive infinite impulse response (IIR) filtering. A novel constraint, called the constant-norm constraint, unifies the quadratic constraint and the monic one. By imposing the monic constraint on the mean square error (MSE) optimization, the merits of both constraints are inherited and the shortcomings are overcome. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of bias-free adaptive IIR filtering algorithms. For example, two efficient algorithms belonging to the family are proposed. The analysis of the stationary points is presented to show that the proposed methods can indeed produce bias-free parameter estimates in the presence of white noise. The simulation results demonstrate that the proposed methods indeed produce unbiased parameter estimation, while being simple both in computation and implementation.

We propose the problem of how to transmit an information-theoretically secure bit using random deals of cards among players in hierarchical groups and a computationally unlimited eavesdropper. A player in the highest group wants to send players in lower groups a secret bit which is secure from the eavesdropper and some other players. We formalize this problem and design protocols for constructing secret key exchange spanning trees on hierarchical groups. For each protocol we give sufficient conditions to successfully construct a secret key exchange spanning tree for the hand sizes of the players and the eavesdropper.