Scattering data from radar targets are analyzed in the time-frequency domain by using wavelet transform, and the scattering mechanisms are investigated. The wavelet transform used here is a powerful tool for the analysis of scattering data, because it can provide better insights into scattering mechanisms that are not immediately apparent in either the time or frequency domain. First, two types of wavelet transforms that are applied to the time domain data and to the frequency domain data are defined, and the multi-resolution characteristics of them are discussed. Next, the scattering data from a conducting cylinder, two parallel conducting cylinders, a parallel-plate waveguide cavity, and a rectangular cavity in the underground are analyzed by using these wavelet transforms to reveal the scattering mechanisms. In the resulting time-frequency displays, the scattering mechanisms including specular reflection, creeping wave, resonance, and dispersion are clearly observed and identified.

We consider methods to locate sync words in packet or frame transmission over the additive white Gaussian noise channel. Our starting point is the maximization of the probability of correctly locating the sync word. We extend Massey's original result to the specific synchronization problem, where the sync words is prefixed to the data stream and each packet is preceded by idle transmission or additive white Gaussian noise. We give simulation results for several interesting sync words such as Barker sequences of length 7 and 13 and a sync word of length 17 with good cross-correlation properties. One of the conclusions is that the newly derived formula for the probability of correctly locating the sync word enables the reduction of the false sync detection probability.

In this paper the conventional symbol-aided estimation methods are extended to use not only the known pilot symbols but also the previously estimated fading values to extract more information on fading channels. The proposed estimation method is evaluated using theoretical analyses. Recursive formulae are derived for calculating the mean square estimation errors, which are then used to calculate the BER performance of a BPSK system employing the proposed fading estimation method. The results show strong BER performance of the proposed system in the region of high signal to noise ratio under fast fading compared to that of the conventional system. Moreover, the proposed system still sustains its performance under mismatched conditions, where the conventional system degrades exhibiting error floors. Finally the theoretical results are verified by using computer simulations.

We investigate an importance sampling (IS) simulation of MMPP/D/1 queueing to obtain an estimate for the survivor function P(Q > q) of the queue length Q in the steady state. In Ref.[11], we studied the IS simulation of 2-state MMPP/D/1 queueing and obtained the optimal simulation distribution, but the mathematical fundation of the theory was not enough. In this paper, we construct a discrete time Markov chain model of the n-state MMPP/D/1 queueing and extend the results of Ref.[11] to the n-state MMPP/D/1. Based on the Markov chain model, we determine the optimal IS simulation distribution fo the n-state MMPP/D/1 queueing by applying the large deviations theory, especially, the sample path large deviations theory. Then, we carry out IS simulation with the obtained optimal simulation distribution. Finally, we compare the simulation results of the IS simulation with the ordinary Monte Carlo (MC) simulation. We show that, in a typical case, the ratio of the computation time of the IS simulation to that of the MC simulation is about 10-7, and the 95% confidence interval of the IS is slightly improved compared with the MC.

Let {Xk}k=- be a stationary and ergodic information source, where each Xk takes values in a standard alphabet A with a distance function d: A A [0, ) defined on it. For each sample sequence X = (, x-1, x0, x1, ) and D > 0 let the approximate D-match recurrence time be defined by Rn (x, D) = min {m n: dn (Xn1, Xm+nm+1) D}, where Xji denotes the string xixi+1 xj and dn: An An [0, ) is a metric of An induced by d for each n. Let R (D) be the rate distortion function of the source {Xk}k=- relative to the fidelity criterion {dn}. Then it is shown that lim supn-1/n log Rn (X, D) R (D/2) a. s.

A method for recovering the LPC spectrum from a microphone array input signal corrupted by less directional ambient noise is proposed. This method is based on the subspace method, in which directional signal and non-directional noise is classified in the subspace domain using eigenvalue analysis of the spatial correlation matrix. In this paper, the coherent subspace (CSS) method, a broadband extension of the subspace method, is employed. The advantage of this method is that is requires a much smaller number of averages in the time domain for estimating subspace, suitable feature for frame processing such as speech recognition. To enhance the performance of noise reduction, elimination of noise-dominant subspace using projection is further proposed, which is effective when the SNR is low and classification of noise and signals using eigenvalue analysis is difficult.

In recently year, the analysis of power management becomes more important. It is difficult to obtain the maximum power because this is NP-complete. For an n-input circuit, there are 22n different input patterns to be considered. There are two major methods for this problem. First method is to generate input patterns to obtain the maximal power by simulating these generated patterns. This method is called pattern based. The other one uses probability method to estimate the power density of each node of a circuit to calculate the maximal power. In this paper, we use a pattern based method to estimate the maximal power. This method is better than that of probability for the simulation of power activity. In practical applications, these generated patterns can be applied and observe the activity of a circuit. These simulated data can be used to examined the critical paths for performance optimization. A simulated annealing algorithm is proposed to search input patterns for maximum power. Firstly, it transforms this problem into an optimization problem to adapt the simulated annealing method. In this method, there are three strategies for generating the next input patterns, called neighborhood. In the first strategy, it generates the next input pattern by changing the status of all input nodes. In the second strategy, some input nodes are selected and changed randomly.

We propose a method to search all the zeros of a complex function in a given compact region D Cn. The function f: Cn Cn to be considered is assumed to consist of polynomial and transcendental terms and to satisfy f (x) Rn for any x Rn. Using the properties of such a complex function, we can compute the number of zeros and determine the starting points of paths on the boundary of D, which attain all the zeros of f in D without encountering a singular point. A piecewiselinear approximation of the function on a triangulation is used for both computing the number of zeros and following the paths.

In this paper, we propose a two-dimensional (2-D) least-squares lattice (LSL) algorithm for the general case of the autoregressive (AR) model with an asymmetric half-plane (AHP) coefficient support. The resulting LSL algorithm gives both order and space recursions for the 2-D deterministic normal equations. The size and shape of the coefficient support region of the proposed lattice filter can be chosen arbitrarily. Furthermore, the ordering of the support signal can be assigned arbitrarily. Finally, computer simulation for modeling a texture image is demonstrated to confirm the proposed model gives rapid convergence.

Clothoid or cornu spiral segments were used as transition spirals forming C-and S-shaped curves between circles as well as straight lines in various situations of highway road design. These transitions are the center lines of rail, highway road design. The above C and S-shaped form curves consist one or more transition segments. We study the possibility of using the single transition spirals in the situations that use many transition spirals to form smooth transition spline between circles as well as straight lines. We also compute the bounds for the scaling of such single spirals using the practical equation. This paper is aimed to give a method avoiding non-linear equations by finding range for the scaling factor of the clothoids which can take initially an appropriate closer value from this range.

The approach presented in this paper was intended for extending conventional Markov random field (MRF) models to a more practical problem: the unsupervised and adaptive segmentation of gray-level images. The "unsupervised" segmentation means that all the model parameters, including the number of image classes, are unknown and have to be estimated from the observed image. In addition, the "adaptive" segmentation means that both the region distribution and the image feature within a region are all location-dependent and their corresponding parameters must be estimated from location to location. We estimated local parameters independently from multiple small windows under the assumption that an observed image consists of objects with smooth surfaces, no texture. Due to this assumption, the intensity of each region is a slowly varying function plus noise, and the conventional homogeneous hidden MRF (HMRF) models are appropriate for these windows. In each window, we employed the EM algorithm for maximum-likelihood (ML) parameter estimation, and then, the estimated parameters were used for "maximizer of the posterior marginals" (MPM) segmentation. To keep continuous segments between windows, a scheme for combining window fragments was proposed. The scheme comprises two parts: the programming of windows and the Bayesian merging of window fragments. Finally, a remerging procedure is used as post processing to remove the over-segmented small regions that possibly exist after the Bayesian merging. Since the final segments are obtained from merging, the number of image classes is automatically determined. The use of multiple parallel windows makes our algorithm to be suitable for parallel implementation. The experimental results of real-world images showed that the surfaces (objects) consistent with our reasonable model assumptions were all correctly segmented as connected regions.

A novel neural network architecture for image texture classification is introduced. The proposed model (Kernel Modifying Neural Network: KM Net) which incorporates the convolution filter kernel and the classifier in one, enables an automated texture feature extraction in multichannel texture classification through the modification of the kernel and the connection weights by the backpropagation-based training rule. The first layer units working as the convolution kernels are constrained to be an array of Gabor filters, which achieves a most efficient texture feature localization. The following layers work as a classifier of the extracted texture feature vectors. The capability of the KM Net and its training rule is verified using a basic problem on a synthetic texture image. In addition, the possibilities of applying the KM Net to natural texture classification and biological tissue classification using an ultrasonic echo image have been tried.

To reduce the memory access latency on sharedmemory multiprocessors, several prefetching schemes have been proposed. The sequential prefetching scheme is a simple hardware-controlled scheme, which exploits the sequentiality of memory accesses to predict which blocks will be read in the near future. Aggressive sequential prefetching prefetches many blocks on each miss to reduce the miss rates and results in good performance for application programs with high sequentiality. However, conservative sequential prefetching prefetches a few blocks on each miss to avoid prefetching of useless blocks, which shows better performance than aggressive sequential prefetching for application programs with low sequentiality. We analyze the relationship between the sequentiality of application programs and the effectiveness of sequential prefetching on various memory and network latency and propose a new adaptive sequential prefetching scheme. Simply adding a small table to the sequential prefetching scheme, the proposed scheme prefetches a large number of blocks for application programs with high sequentiality and reduces the miss rates significantly, and prefetches a small number of blocks for application programs with low sequentiality and avoids loading useless blocks.

This paper proposes a general expansion architecture for constructing large-scale multicast ATM switches with any type of small multicast switch, called the multicast Universal Multistage Interconnection Network (multicast UniMIN). The proposed architecture consists of a buffered distribution network that can perform cell routing and replication simultaneously, and a column of output switch modules (OSMs). The adoption of channel grouping and virtual first-in-first-out (FIFO) buffers results in high delay/throughput performance, and the distributed lookup table scheme for multicast addressing greatly reduces the size of a single lookup table. Analytical and simulation results show that high delay/throughput performance is obtained for both unicast and multicast traffic, and the proposed architecture yields an even better performance for multicast traffic than for unicast traffic. In addition, the multicast UniMIN switch has such good features as modular expandability, simple hardware, and no internal speed-up operation.

In this paper, we propose a new multicast routing algorithm for constructing the delay-constrained minimal spanning tree in the VP-based ATM networks, in which we consider the efficiency even in the case where the destination dynamically joins/departs the multicast connection. For constructing the delay-constrained spanning tree, we first generate a reduced network consisting of only VCX nodes from a given ATM network, originally consisting of VPX/VCX nodes. Then, we obtain the delay-constrained spanning tree with a minimal tree cost on the reduced network by using our proposed heuristic algorithm. Through numerical examples, we show that our dynamic multicast routing algorithm can provide an efficient usage of network resources when the membership nodes frequently changes during the lifetime of a multicast connection, while the existing multicast routing algorithm may be useful for constructing the multicast tree with a static nature of destination nodes. We also demonstrate that more cost-saving can be expected in dense networks when applying our proposed algorithm.

This paper analyzes mechanisms of radiated emissions from multilayer printed circuit boards (PCBs) and presents a model to describe the characteristics of such radiation. The radiation mechanism from a four-layer PCB, including the internal power and ground planes, is investigated using a time-domain magnetic field measurement near the PCB. Measurement of the waveform indicates that the main source of radiation is in the power distribution planes. To investigate the characteristics of the radiation from the power distribution, the S21s of the board are measured; the board impedance and the transmission characteristics of the power distribution planes are found to be directly related to the S21 between the two points in the board. The results indicate that the power distribution acts as a transmission line at frequencies higher than 100 MHz. A model that can explain well the radiation properties of these planes treats them as a parallel-plate transmission line interconnected by decoupling circuit comprising a decoupling capacitor and interconnect inductance. From the transmission line theory it is deduced that the line resonance gives rise to strong radiated emissions. The interconnect inductance is an important factor in determining the radiation characteristics.

This paper presents a new upper bound on overall bit error rate (BER) for a concatenated code which consists of an inner convolutional code and an outer interleaved Reed-Solomon code. The upper bound on BER is derived based on a lower bound on the effective minimum distance of the concatenated code. This upper bound can be used for the cases when the interleaver size is small such that the conventional upper bound is not applicable.

Turbo codes have fascinated many coding researchers because of thier near-Shannon-limit error correction performance. In this paper, we discuss multi-dimensional turbo codes which are parallel concatenation of multiple constituent codes. The average upper bound to bit error probability of multidimensional turbo codes is derived. The bound shows that the interleaver gains of this kind of codes are larger than that of conventional two-dimensional turbo codes. Simplified structures of multi-dimensional turbo encoder and decoder are proposed for easier implementation. Simulation results show that for a given interleaver size, by increasing the dimension, great performance improvement can be obtained.

Generalized minimum-distance (GMD) decoding is well-known as a soft decision decoding technique for such linear block codes as BCH and RS codes. The GMD decoding algorithm generates a set of candidate codewords and selects as a decoded codeword that candidate with the smallest reliable distance. In this paper, for a GMD decoder of RS and BCH codes, we present a new sufficient condition for the decoded codeword to be optimal, and we show that this sufficient condition is less stringent than the one presented by Taipale and Pursely.

Recently, progress has been made in the area of electrical modeling of conductors embedded in arbitrary dielectrics using circuit oriented techniques. These models usually occur in conjunction with VLSI type circuits. Many different applications exist today for such models in the EMI, EIP (Electrical Interconnect and Package) analysis as well as for the microwave circuit area. Practical problems involve a multitude of hardware components and they demand a wide spectrum of both time as well as frequency domain solution techniques. In this paper we consider circuit oriented techniques for the solution of these problems. Specifically, we give an outline of the three dimensional Partial Element Equivalent Circuit (PEEC) full wave modeling approach and review the recent progress in this area.