An efficient finite element-integral equation method is presented for calculating scattered fields from conducting objects. By combining the integral equation solution with the finite element method, this formulation allows a finite element computational domain terminated very closely to the scatterer and thus results in the decrease of the resultant matrix size. Furthermore, we employ a new integral approach to establish the boundary condition on the finite element terminating surface. The expansion of the fields on the integration contour is not related to the fields on the terminating surface, hence we obtain an explicit expression of the boundary condition on the terminating surface. Using this explicit boundary condition with the finite element solution, our method substantially improves the computational efficiency and relaxes the computer memory requirements. Only one matrix inversion is needed through our formulation and the generation and storing of a full matrix is not necessary as compared with the conventional hybrid finite element methods. The validity and accuracy of the formulation are checked by some numerical solutions of scattering from two-dimensional metallic cylinders, which are compared with the results of other methods and/or measured data.

Unequal error protection (UEP) is a very promising coding technique for satellite broadcasting, as it gradually reduces the transmission rate. From the viewpoint of bandwidth efficiency, UEP should be achieved in the context of multilevel coded modulation. However, the conventional mapping between encoded bits and modulation signals, usually realized for multilevel block modulation codes and multistage decoding, is not very compatible with UEP coding because of the large number of resulting nearest neighbor codewords. In this paper, new coded modulation schemes for UEP based on unconventional partitioning are proposed. A linear operation referred to as interlevel combination is introduced. This operation generalizes previous partitioning proposed for UEP applications and provides additional flexibility with respect to UEP capabilities. The error performance of the proposed codes are evaluated both by computer simulations and a theoretical analysis. The obtained results show that the proposed codes achieve good tradeoff between the proportion and the error performance of each error protection level.

This paper proposes and investigates a coding and decoding scheme to achieve adaptive unequal error protection (UEP) using several convolutional codes which have different error-correcting capabilities. An appropriate encoder is selected to unequally protect each frame of information sequence according to the importance of the frame. Since the supplemental information of selected encoder is not sent for the sake of reducing redundancy, we assume that the decoder does not know which encoder was used, and the decoder has to estimate the used encoder. In order to estimate which encoder was used, the method using biased metric in Viterbi decoding is proposed. In decoding, however, there is a problem of Decoder-Selection-Error (DSE), which is an error that the decoder selected in a receiver does not correspond to the encoder used in a transmitter. An upper bound of DSE rate in decoding is derived. The proposed decoding scheme using the biased metric in a trellis can improve DSE rate and BER performance, because transition probability of encoders is taken into account in calculating likelihood by means of making branch or path metric biased. Computer simulation is employed to evaluate the BER performance and DSE rate of the proposed scheme. The performance is compared with a conventional equal error protection scheme and a UEP with the supplemental information on the used encoder. It is found that the proposed scheme can achieve better performance than them in case N=2.

In this paper, we study unequal error protection (UEP) capabilities of punctured convolutional codes. For constructing the good UEP convolutional codes, the conditional weight distributions of UEP convolutional codes are defined and evaluated. The conditional weight distributions are computed by using the transfer functions of time-varying trellis structures of punctured convolutional codes. The best UEP convolutional codes from the viewpoint of the weight distributions are listed.

Recently, Garcia and Stichtenoth proposed sequences of algebraic function fields with finite constant fields such that their sequences attain the Drinfeld-Vl bound. In the sequences, the third algebraic function fields are Artin-Schreier extensions of Hermitian function fields. On the other hand, Miura presented powerful tools to construct one-point algebraic geometric (AG) codes from algebraic function fields. In this paper, we clarify rational functions of the third algebraic function fields which correspond to generators of semigroup of nongaps at a specific place of degree one. Consequently, we show generator matrices of the one-point AG codes with respect to the third algebraic function fields for any dimension by using rational functions of monomial type and rational points.

This paper proposes a high-speed connection admission control scheme, named PERB CAC (CAC based on Prior Estimation for Residual Bandwidth). This scheme estimates the residual bandwidth in advance by generating a series of virtual requests for connection. When an actual connection request occurs, PERB CAC can instantaneously judge if the required bandwidth is larger than the estimated residual bandwidth, so the connection set-up time can be greatly reduced. Therefore, PERB CAC can realize high-speed connection set-up.

We present two types of ICF (INHIBIT Controlled by Fluxon) gates as the basic circuits of the phase-mode logic family, and fabricate an adder circuit. The experimental result demonstrates that the carry operation followed up to 99 GHz input pulses. The performance of Josephson devices is improved by the use of junctions with high current density (Jc). We may use the high-Jc junctions without external resistive shunt in the phase-mode logic circuits because of reduction of the junction hysteresis. One of the ways to overcome the large area occupancy for geometric inductance is to utilize the effective inductance of a Josephson junction itself. We investigate a circuit construction with high-Jc inductor junctions, intrinsically overdumped junctions and junction-type resistors for the compactness of circuit integration, and discuss various aspects of the circuit construction.

The development of saturation diving in civil and defense applications has enabled man to work in the sea at great depths and for long periods of time. This advance has resulted, in part, as a consequence of the substitution of helium for nitrogen in breathing gas mixtures. However, utilization of HeO2 breathing mixture at high ambient pressures has caused problems in speech communication; in turn, helium speech enhancement systems have been developed to improve diver communication. These speech unscramblers attempt to process variously the grossly unintelligible speech resulting from the effect of breathing mixtures and ambient pressure, and to reconstruct such signals in order to provide adequate voice communication. It is known that the glottal excitation is quasi-periodic and the vocal tract filter is quasi-stationary. Hence, it is possible to use an auto regressive modelisation to restore speech intelligibility in hyperbaric conditions. Corrections are made on the vocal tract transfer function, either in the frequency domain, or directly on the autocorrelation function. A spectral subtraction or noise reduction may be added to improve speech quality. A new VAD enhanced helium speech unscrambler is proposed for use in adverse conditions or in speech recognition. This system, implementable on single chip DSP of current technology, is capable to work in real time.

This paper proposes an object oriented face region detection and tracking method using range color information. Range segmentation of the objects are obtained from the complicated background using disparity histogram (DH). The facial regions among the range segmented objects are detected using skin-color transform technique that provides a facial region enhanced gray-level image. Computationally efficient matching pixel count (MPC) disparity measure is introduced to enhance the matching accuracy by removing the effect of the unexpected noise in the boundary region. Redundancy operations inherent in the area-based matching operation are removed to enhance the processing speed. For the skin-color transformation, the generalized facial color distribution (GFCD) is modeled by 2D Gaussian function in a normalized color space. Disparity difference histogram (DDH) concept from two consecutive frames is introduced to estimate the range information effectively. Detailed geometrical analysis provides exact variation of range information of moving object. The experimental results show that the proposed algorithm works well in various environments, at a rate of 1 frame per second with 512 480 resolution in general purpose workstation.

This paper presents a method which can effectively acquire free space on a plane for moving forward in safety by using height information of objects. This method can be applied to free space extraction on a road, and, in short, it is a road extraction method for an autonomous vehicle. Since a road area can be assumed to be a sequence of flat planes in front of a vehicle, it is effective to apply the inverse perspective projection model to the ground plane. However, conventional methods using this model have a drawback in that some areas on the road plane are wrongly detected as obstacle areas since these methods are sensitive to the error of the camera geometry with respect to the assumed plane. In order to overcome this drawback, the proposed approach named the Planar Projection Stereopsis (PPS) method supplies, to the road extraction method using the inverse perspective projection model, a contrivance for removing these erroneous areas effectively. Since PPS uses the inverse perspective projection model, both left and right images are projected to the road plane and obstacle areas are detected by examining the difference between these projected images. Because detected obstacle areas include a lot of erroneous areas, PPS examines the shapes of the obstacle areas and eliminates falsely detected areas on the road plane by using the following properties: obstacles whose heights are different from the road plane are projected to the shapes falling backward from the location where the obstacles touch the road plane; and the length of shapes falling backward depends on the location of obstacles in relation to the stereoscopic cameras and the height of obstacles in relation to the road plane. Experimental results for real road scenes have shown the effectiveness of the proposed method. The quantitative evaluation of the results has shown that on average 89. 3% of the real road area can be extracted and the average of the falsely extracted ratio is 1. 4%. Since the road area can be extracted by simple projection of images and subtraction of projected images from a set of stereo images, our method can be applied to real-time operation.

This paper proposes a simple learning algorithm that can realize any boolean function using the three-layer binary neural networks. The algorithm has flexible learning functions. 1) moving "core" for the inputs separations,2) "don't care" settings of the separated inputs. The "don't care" inputs do not affect the successive separations. Performing numerical simulations on some typical examples, we have verified that our algorithm can give less number of hidden layer neurons than those by conventional ones.

This paper proposes Emergent Behavior Based Architecture (EBBA) that fusions heterogeneous sensor information at the level of behavior modules. The characteristics of EBBA are as follows. i) sensor based architecture, ii) constructed by a set of concurrently executable behavior modules, iii) to have multiple methods to achieve given tasks by utilizing behavior modules, iv) a planner can control emergent behaviors. We also have developed mobile robot navigation system based on EBBA and confirmed the efficiency by experiments in the various situations.

We present a cascade neural network for blind source extraction. We propose a family of unconstrained optimization criteria, from which we derive a learning rule that can extract a single source signal from a linear mixture of source signals. To prevent the newly extracted source signal from being extracted again in the next processing unit, we propose another unconstrained optimization criterion that uses knowledge of this signal. From this criterion, we then derive a learning rule that deflates from the mixture the newly extracted signal. By virtue of blind extraction and deflation processing, the presented cascade neural network can cope with a practical case where the number of mixed signals is equal to or larger than the number of sources, with the number of sources not known in advance. We prove analytically that the proposed criteria both for blind extraction and deflation processing have no spurious equilibria. In addition, the proposed criteria do not require whitening of mixed signals. We also demonstrate the validity and performance of the presented neural network by computer simulation experiments.

This paper describes an efficient simulation algorithm for the spatiotemporal pattern analysis of the continuous-time neural networks with the multivalued logic (multivalued continuous-time neural networks). The multivalued transfer function of neuron is approximated to the stepwise constant function which is constructed by the sum of the step functions with the different thresholds. By this approximation, the dynamics of the network can be formulated as a stepwise constant linear differential equation at each timestep and the optimal timestep for the numerical integration can be obtained analytically. Finally, it is shown that the proposed method is much faster than a variety of conventional simulators.

Modeling error is the major concerning issue in the trajectory estimation. This paper formulates the dynamic model of a reentry vehicle in reentry phase for identification with an unmodeled acceleration input covering possible model errors. Moreover, this work presents a novel on-line estimation approach, adaptive filter, to identify the trajectory of a reentry vehicle from a single radar measured data. This proposed approach combines the extended Kalman filter and the recursive least-squares estimator of input with the hypothetical testing scheme. The recursive least-squares estimator is provided not only to extract the magnitude of the unmodeled input but to offer a testing criterion to detect the onset and presence of the input. Numerical simulation demonstrates the superior capabilities in accuracy and robustness of the proposed method. In real flight analysis, the adaptive filter also performs an excellent estimation and prediction performances. The recommended trajectory estimation method can support defense and tactical operations for anti-tactical ballistic missile warfare.

This letter presents a new algorithm for improving the Signal to Noise Ratio (SNR) of complex sinusoidal signals contaminated by additive Gaussian noises using sum of Higher-Order Statistics (HOS). We conduct some computer simulations to show that the proposed algorithm can improve the SNR more than 7 dB compared with the conventional coherent integration when the SNR of the input signal is -10 dB.

The most basic cross-talk minimization problem is to assign given n intervals to n parallel tracks where the cross-talk is defined between two intervals assigned to the adjacent tracks with the amount linear to parallel running length. This paper solves the problem for the case when any pair of intervals intersects and the objective is to minimize the sum of cross-talks. We begin the discussion with the fact that twice the sum of lengths of n/2 shortest intervals is a lower bound. Then an interval set that attains this lower bound is characterized with a simple assignment algorithm. Some additional considerations provide the minimum cross-talk for the other interval sets. The main procedure is to sort the intervals twice with respect to the length of left and right halves of intervals.

In this paper, we show that two-dimensional billiards with point interactions inside exhibit a chaotic nature in the microscopic world, although their classical counterpart is non-chaotic. After deriving the transition matrix of the system by using the self-adjoint extension theory of functional analysis, we deduce the general condition for the appearance of chaos. The prediction is confirmed by numerically examining the statistical properties of energy spectrum of rectangular billiards with multiple point interactions inside. The dependence of the level statistics on the strength as well as the number of the scatterers is displayed.

Complex rule conditions are commonly required to describe complicated business semantics. In these cases, efficient condition evaluation is crucial for high performance of active database systems. Most previous works used the incremental evaluation techniques, whose operations are relatively expensive due to the processing based on the exact calculation of the condition expression. In this paper we propose a new filtering technique that effectively identifies false condition in an early stage of condition monitoring. Since the results of condition evaluation tend to be false in most practical cases, an efficient filtering method can highly facilitate fast condition evaluation. The proposed filtering technique is developed based on the new perspective of database state and database operations, i. e. , a vector space model. We first present vector representations of database states, database operations, and complex condition expressions. Then, we propose a filtering method based on the properties of a vector space, called the sphere containment test. Our proposed method determines the truth value of the rule conditions only with the delta vectors maintained in main memory. We compare our method with a typical incremental evaluation method and show that the proposed method can give a significant performance enhancement.

This article shows that a multivalued logic defined as juxtaposition of Boolean binary logics can use all of inference chain, induction and deduction that are important in realization of intelligent inference systems.