To develop human interfaces such as home information equipment, highly capable word learning ability is required. In particular, in order to realize user-customized and situation-dependent interaction using language, a function is needed that can build new categories online in response to presented objects for an advanced human interface. However, at present, there are few basic studies focusing on the purpose of language acquisition with category formation. In this study, taking hints from an analogy between machine learning and infant developmental word acquisition, we propose a taxonomy-based word-learning model using a neural network. Through computer simulations, we show that our model can build categories and find the name of an object based on categorization.

Variable-coefficient generalizations of integrable nonlinear equations are one of exciting subjects in the study of mechanical, physical, mathematical and engineering sciences. In this paper, we present a KdV family (namely, KdV, modified KdV, Calogero-Degasperis-Fokas and Harry-Dym equations) with variable coefficients in (2 + 1) dimensions.

This paper focuses on developing a square root (SQRT) algorithm in finite fields GF(p2d) (d 0). Examining the Smart algorithm, a well-known SQRT algorithm, we can see that there is some computation overlap between the Smart algorithm and the quadratic residue (QR) test, which must be implemented before a SQRT computation. It makes the Smart algorithm inefficient. In this paper, we propose a new QR test and a new SQRT algorithm in GF(p2d), in which not only there is no computation overlap, but also most of computations required for the proposed SQRT algorithm in GF(p2d) can be implemented in the corresponding subfields GF(p2d-i) for 1 i d, which yields many reductions in the computational time and complexity. The computer simulation also shows that the proposed SQRT algorithm is much faster than the Smart algorithm.

In this paper, we propose a broadband 3-dB rat-race ring coupler that uses tightly coupled lines. An aperture compensation technique that can simplify the fabrication of tightly coupled lines, is also discussed here. The effective bandwidth of the proposed rat-race coupler with a return loss better than -20 dB can be increased by 14.3%, in comparison with that of March's. Its isolation is always below -20 dB and the phase shift errors less than 6.

In this paper, it is proved that there is a transformation between two types of nonlinear feedback shift register which can be regarded as implementation of the Bernoulli and tent maps with finite precision. This transformation can be interpreted as a sort of finite dimension version of topological conjugation between the Bernoulli and tent maps on continuous phase space. Several properties of periodic sequences generated from extended NFSRs are derived from the relation.

This paper aims at challenging Bernstein's problem called the "Degrees-of-Freedom problem," which remains unsolved from both the physiological and robotics viewpoints. More than a half century ago A.N. Bernstein observed that "dexterity" residing in human limb motion emerges from accumulated involvement of multi-joint movements in surplus DOF. It is also said in robotics that redundancy of DOFs in robot mechanisms may contribute to enhancement of dexterity and versatility. However, kinematic redundancy incurs a problem of ill-posedness of inverse kinematics from task-description space to joint space. In the history of robotics research such ill-posedness problem of inverse-kinematics has not yet been attacked directly but circumvented by introducing an artificial performance index and determining uniquely an inverse kinematics solution by minimizing it. Instead of it, this paper introduces two novel concepts named "stability on a manifold" and "transferability to a submanifold" in treating the case of human multi-joint movements of reaching and shows that a sensory feedback from task space to joint space together with a set of adequate dampings enables any solution to the overall closed-loop dynamics to converge naturally and coordinately to a lower-dimensional manifold describing a set of joint states fulfilling a given motion task. This means that, without considering any type of inverse kinematics, the reaching task can be accomplished by a sensory feedback with adequate choice of a stiffness parameter and damping coefficients. It is also shown that these novel concepts can cope with annoying characteristics called "variability" of redundant joint motions seen typically in human skilled reaching. Finally, it is pointed out that the proposed control signals can be generated in a feedforward manner in case of human limb movements by referring to mechano-chemical characteristics of activation of muscles. Based on this observation, generation of human skilled movements of reaching can be interpreted in terms of the proposed "Virtual-Spring" hypothesis instead of the traditional "Equilibrium-Point" hypothesis.

Grid computing is a state-of-the-art parallel computing technology which enables worldwide computers to dynamically share their computing powers and resource to each other. The grid takes advantage of Internet as a universal communication platform to carry messages. Basically, Internet doesn't guarantee loss-free and ordered transmission, hence, the grid should keep the cause and effect of events by itself to ensure the correct ordering of command invocations at the remote hosts. The ordering issue arises when the messages travel across the networks with unpredictable delay. Recent research has studied the security and resource control issues, but failed to address the requirements of transport layer on the grid communication platform. In this paper, we propose the Causal Ordered Grid (COG) architecture and implement it to study the transport performance issues when the grid is built over worldwide networks. The COG provides a novel service model to the applications with time-sensitive and causal-ordered transportation. From our experiments, the design of the grid middleware should use a causal-ordered, time-sensitive transportation rather than TCP. Our research will be beneficial to the improvement of the grid computing and can provide wealthy empirical results for the designer.

In this paper, we propose a single-user strategy for demodulating asynchronous direct-sequence code-division multiple access (DS/CDMA) signals for improving the performance of the adaptive receiver in fast fading channels. Since the adaptive receiver depends on the channel coefficient of all users, it cannot be implemented adaptively in fading channels due to severe tracking problem. A proposed adaptive receiver based on the modified minimum mean-squared-error (MMSE) criterion is used for solving this problem. By simulation, it is verified that our proposal is a promising method to solve the problem, and the results show that the proposed adaptive receiver has substantially larger capacity than the conventional adaptive receiver in fast fading channels.

In this paper, we address how to efficiently support differentiated services with the optimized bandwidth reservation in a polling-based generalized TDMA network like E-PON (Ethernet Passive Optical Network). In E-PON, performances of service differentiation for QoS (Quality of Service) guaranteed multiples services are directly affected by the bandwidth reservation algorithm of ONU (Optical Network Unit) in addition to the priority-based packet scheduling. Our proposed Service Quality Pre-engagement (SQP) algorithm reduces the system buffer size, the light-load penalty problem and the service interference among classes effectively by partially introducing the dynamic forward recurrence reservation scheme for QoS guaranteed classes. We also introduce the FRC(Forward Reservation Class) Selection algorithm that preserves the optimized reservation bandwidth to minimize the unnecessary reservation contentions. These algorithms do not mandate the basic concept of DBA and request the similar amount of REPORT bandwidth. The analytic and simulation results are performed to evaluate the performances of the proposed algorithms.

A new low power test pattern generator (TPG) which can effectively reduce the average power consumption during test application is developed. The new TPG reduces the weighted switching activity (WSA) of the circuit under test (CUT) by suppressing transitions at some primary inputs which make many transitions. Moreover, the new TPG does not lose fault coverage. Experimental results on the ISCAS benchmark circuits show that average power reduction can be achieved up to 33.8% while achieving high fault coverage.

In this paper, we shall construct mathematical theory based on the concept of set-valued mappings, suitable for available operation of extraordinarily complicated large-scale network systems by introducing some connected-block structures. A fine estimation technique for availability of system behaviors of such network systems are obtained finally in the form of fixed point theorem for a special system of fuzzy-set-valued mappings.

There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.

A novel digital redesign methodology based on evolutionary programming (EP) is introduced to find the 'best' digital controller for optimal tracking design of hybrid uncertain multi-input/ multi-output (MIMO) input-delay systems with constraints on states and controls. To deal with these multivariable concurrent specifications and system restrictions, instead of conventional interval methods, the proposed global optimization scheme is able to practically implement optimal digital controller for constrained uncertain hybrid systems with input time delay. Further, an illustrative example is included to demonstrate the efficiency of the proposed method.

The lifting scheme is an efficient and flexible method for the construction of linear and nonlinear wavelet transforms. In this paper, a novel lossless image coding technique based on the lifting scheme using discrete-time cellular neural networks (DT-CNNs) is proposed. In our proposed method, the image is interpolated by using the nonlinear interpolative dynamics of DT-CNN, and since the output function of DT-CNN works as a multi-level quantization function, our method composes the integer lifting scheme for lossless image coding. Moreover, the nonlinear interpolative dynamics by A-template is used effectively compared with conventional CNN image coding methods using only B-template. The experimental results show a better coding performance compared with the conventional lifting methods using linear filters.

Though block-based motion estimation techniques are primarily designed for video coding applications, they are increasingly being used in other video analysis applications due to their simplicity and ease of implementation. The major drawback associated with these techniques is that noises, in the form of false motion vectors, cannot be avoided while capturing block motion vectors. Similar noises may further be introduced when the technique of global motion compensation is applied to obtain true object motion from video sequences where both the camera and object motions are present. This paper presents a new technique for capturing large number of true object motion vectors by eliminating the false motion vector fields, for use in the application of object motion based video indexing and retrieval applications. Experimental results prove that our proposed technique significantly increases the percentage of retained true object motion vectors while eliminating all false motion vectors for variety of standard and non-standard video sequences.

Multilayered filters with a dielectric distribution along their thickness forming a one-dimensional quasi-fractal structure are theoretically analyzed, focusing on exposing their resonant properties in order to understand a dielectric Menger's sponge resonator [4],[5]. "Quasi-fractal" refers to the triadic Cantor set with finite generation. First, a novel calculation method that has the ability to deal with filters with fine fractal structures is derived. This method takes advantage of Clifford algebra based on the theory of thin-film optics. The method is then applied to classify resonant modes and, especially, to investigate quality factors for them in terms of the following design parameters: a dielectric constant, a loss tangent, and a stage number. The latter determines fractal structure. Finally, behavior of the filters with perfect fractal structure is considered. A crucial finding is that the high quality factor of the modes is not due to the complete self-similarity, but rather to the breaking of such a fractal symmetry.

This paper proposes a Java online plug-in mechanism that can be used to modify any part in a system file coded in Java, even while the part is running, without service interruption. The Java-related plug-in capabilities are devised by using the plug-in functional elements offered by the existing C++ online plug-in that we proposed. In particular, measures on how to deal with the use of Just In Time compilation and inline expansion are considered. New linkage and file-back up techniques are proposed for this purpose. Case studies reveal its wide applicability and the degree of memory area saving effects. Evaluation proves this mechanism does not affect the performance of ordinary service processing. It is expected to be used in practice for Java-based service processing such as VoIP and Instant Messaging.

The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process.

This paper presents designs and performances of 76 GHz band alternating-phase fed single-layer slotted waveguide arrays. Two kinds of design, that is, uniform aperture illumination for maximum gain and Taylor distribution for sidelobe suppression of -25 dB, are conducted. High gain and high efficiency performance of 34.8 dBi with 57% is achieved for the former, while satisfactory sidelobe suppression of -20 dB in the H-plane and -23 dB in the E-plane with high efficiency is confirmed for the latter. The simple structure dispensing with electrical contact between the slotted plate and the groove feed structure is the key advantage of alternating-phase fed arrays and the slotted plate is just tacked on the feed structure with screws at the periphery. High gain and high efficiency performances predicted theoretically as well as design flexibility of the alternating-phase fed array are demonstrated in the millimeter wave frequency.

This paper presents a novel method of structure selection and identification for Hammerstein type nonlinear systems. An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The connection coefficients of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. The adjusting parameters for the ACF model structure, i.e. the number and widths of the subdomains and the shape of the ACF are properly selected by using a genetic algorithm, in which the Akaike information criterion is utilized as the fitness value function. The effectiveness of the proposed method is confirmed through numerical experiments.