This paper presents a multi-matcher on-line signature verification system which fuses the verification scores in pen-position parameter and pen-movement angle one at total decision. Features of pen-position and pen-movement angle are extracted by the sub-band decomposition using the Discrete Wavelet Transform (DWT). In the pen-position, high frequency sub-band signals are considered as individual features to enhance the difference between a genuine signature and its forgery. On the other hand, low frequency sub-band signals are utilized as features for suppressing the intra-class variation in the pen-movement angle. Verification is achieved by the adaptive signal processing using the extracted features. Verification scores in the pen-position and the pen-movement angle are integrated by using a weighted sum rule to make total decision. Experimental results show that the fusion of pen-position and pen-movement angle can improve verification performance.

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.

Though there are intensive researches on off-line electronic cash (e-cash), the current computer network infrastructure sufficiently accepts on-line e-cash. The on-line means that the payment protocol involves with the bank, and the off-line means no involvement. For customers' privacy, the e-cash system should satisfy unlinkability, i.e., any pair of payments is unlinkable w.r.t. the sameness of the payer. In addition, for the convenience, exact payments, i.e., the payments with arbitrary amounts, should be also able to performed. In an existing off-line system with unlinkable exact payments, the customers need massive computations. On the other hand, an existing on-line system does not satisfy the efficiency and the perfect unlinkability simultaneously. This paper proposes an on-line system, where the efficiency and the perfect unlinkability are achieved simultaneously.

This paper presents a model and its effect for on-line handwritten Japanese text recognition free from line-direction constraint and writing format constraint such as character writing boxes or ruled lines. The model evaluates the likelihood composed of character segmentation, character recognition, character pattern structure and context. The likelihood of character pattern structure considers the plausible height, width and inner gaps within a character pattern that appear in Chinese characters composed of multiple radicals (subpatterns). The recognition system incorporating this model separates freely written text into text line elements, estimates the average character size of each element, hypothetically segments it into characters using geometric features, applies character recognition to segmented patterns and employs the model to search the text interpretation that maximizes likelihood as Japanese text. We show the effectiveness of the model through recognition experiments and clarify how the newly modeled factors in the likelihood affect the overall recognition rate.

This paper describes an on-line handwritten Japanese text recognition system that is liberated from constraints on line direction and character orientation. The recognition system first separates freely written text into text line elements, second estimates the line direction and character orientation using the time sequence information of pen-tip coordinates, third hypothetically segment it into characters using geometric features and apply character recognition. The final step is to select the most plausible interpretation by evaluating the likelihood composed of character segmentation, character recognition, character pattern structure and context. The method can cope with a mixture of vertical, horizontal and skewed text lines with arbitrary character orientations. It is expected useful for tablet PC's, interactive electronic whiteboards and so on.

In this paper, we propose a new on-line adaptive relaxation algorithm for an inverse filter in a multichannel sound reproduction system. The fluctuation of room transfer functions degrades reproduced sound in conventional sound reproduction systems in which the coefficients of the inverse filter are fixed. In order to resolve this problem, an iterative relaxation algorithm for an inverse filter performed by truncated singular value decomposition (adaptive TSVD) has been proposed. However, it is difficult to apply this method within the time duration of the sound of speech or music in the original signals. Therefore, we extend adaptive TSVD to an on-line-type algorithm based on the observed signal at only one control point, normalizing the observed signal with the original sound. The result of the simulation using real environmental data reveals that the proposed method can always carry out the relaxation process against acoustic fluctuation, for any time duration. Also, subjective evaluation in the real acoustic environment indicates that the sound quality improves without degrading the localization.

Zero-suppressed BDDs (ZBDDs) have been used in the nonenumerative path delay fault (PDF) grading of VLSI circuits. One basic and one cut-based grading algorithm are proposed to grade circuits with polynomial and exponential number of PDFs, respectively. In this article, we present a new ZBDD-based basic PDF grading algorithm to enable grading of some circuits with exponential number of PDFs without using the cut-based algorithm. The algorithm overcomes the memory overflow problems by dynamically pruning the ZBDD at run-time. This new algorithm may give exact or pessimistic coverage depending on the statuses of the pruned nodes. Furthermore, we re-assess the performance of the static variable ordering heuristics in ZBDDs for PDF coverage calculation. The proposed algorithm combined with the efficient static variable ordering heuristics can avoid ZBDD size explosion in many circuits. Experimental results for ISCAS85 benchmarks show that the proposed algorithm efficiently grades circuits.

Authenticated Key Establishment (AKE) protocols enable two entities, say a client (or a user) and a server, to share common session keys in an authentic way. In this paper, we review the previous AKE protocols, all of which turn out to be insecure, under the following realistic assumptions: (1) High-entropy secrets that should be stored on devices may leak out due to accidents such as bugs or mis-configureations of the system; (2) The size of human-memorable secret, i.e. password, is short enough to memorize, but large enough to avoid on-line exhaustive search; (3) TRM (Tamper-Resistant Modules) used to store secrets are not perfectly free from bugs and mis-configurations; (4) A client remembers only one password, even if he/she communicates with several different servers. Then, we propose a simple leakage-resilient AKE protocol (cf.[41]) which is described as follows: the client keeps one password in mind and stores one secret value on devices, both of which are used to establish an authenticated session key with the server. The advantages of leakage-resilient AKEs to the previous AKEs are that the former is secure against active adversaries under the above-mentioned assumptions and has immunity to the leakage of stored secrets from a client and a server (or servers), respectively. In addition, the advantage of the proposed protocol to is the reduction of memory size of the client's secrets. And we extend our protocol to be possible for updating secret values registered in server(s) or password remembered by a client. Some applications and the formal security proof in the standard model of our protocol are also provided.

Power distribution in multilayered periodic waveguides is first analyzed by longitudinal modal transmission-line theory (L-MTLT). Novel effective characteristic impedances of the equivalent network for TE and TM modes are then derived, and a symmetrical grating guide with three layers is rigorously evaluated to clarify the validity of our approach. Excellent agreement between our results and the results due to other methods indicates that our approach is able to not only reveal all the physical meaning embedded in the multilayered and multi-sectional periodic waveguides, but also predict various possible Bragg regimes rigorously and simply.

One of the disadvantages of using OFDM is the larger peak to averaged power ratio (PAPR) of the time domain signal as compared with the conventional single carrier transmission method. The OFDM signal with larger PAPR will cause the undesirable spectrum re-growth and the larger degradation of bit error rate (BER) performance both due to the inter-modulation products occurring in the non-linear amplifier at the transmitter. The clipping method in conjunction with the Decision Aided Reconstruction (DAR) method is well known as one of the solutions to improve the BER performance with keeping the better PAPR performance. However, the DAR method is proposed to mitigate only the clipping noise and not for the inter-modulation noise. In this paper, we propose the Improved DAR (IDAR) method, which can mitigate both the clipping noise and inter-modulation noise on the basis of DAR method. The proposed method enables the efficient usage of transmission power amplifier at the transmitter with keeping the better PAPR and BER performances. This paper presents various computer simulation results to verify the performance of proposed IDAR method in the non-linear channel.

In this work we give an extension of Kauffman's NK-Landscapes to multiobjective MNK-Landscapes in order to study the effects of epistasis on the performance of multiobjective evolutionary algorithms (MOEAs). This paper focuses on the development of multiobjective random one-bit climbers (moRBCs). We incrementally build several moRBCs and analyze basic working principles of state of the art MOEAs on landscapes of increased epistatic complexity and number of objectives. We specially study the effects of Pareto dominance, non-dominance, and the use of memory and a population to influence the search. We choose an elitist non-dominated sorting multiobjective genetic algorithm (NSGA-II) as a representative of the latest generation of MOEAs and include its results for comparison. We detail the behavior of the climbers and show that population based moRBCs outperform NSGA-II for all values of M and K.

A moment matrix analysis (MMA) method can derive macroscopic statistical properties such as moments, response time, and power spectra of non-linear equations without solving the equations. MMA expands a non-linear equation into simultaneous linear equations of moments, and reduces it to a linear equation of their coefficient matrix and a moment vector. We can analyze the statistical properties from the eigenvalues and eigenvectors of the coefficient matrix. This paper presents (1) a systematic procedure to linearize non-linear equations and (2) an expansion of the previous work of MMA to derive the statistical properties of various non-linear equations. The statistical properties of the logistic map were evaluated by using MMA and computer simulation, and it is shown that the proposed systematic procedure was effective and that MMA could accurately approximate the statistical properties of the logistic map even though such a map had strong non-linearity.

In this paper, we present an efficient method to budget on-chip decoupling capacitors (decaps) to optimize power delivery networks in an area efficient way. Our algorithm is based on an efficient gradient-based non-linear programming method for searching the solution. Our contributions are an efficient gradient computation method (time-domain merged adjoint network method) and a novel equivalent circuit modeling technique to speed up the optimization process. Experimental results demonstrate that the algorithm is capable of efficiently optimizing very large scale P/G networks.

In the formerly proposed theory for sub-linear (linear in a changed addition rule) systems, we developed a sub-linear mathematical theory and demonstrated its capability in several sub-linear systems. In this paper, we assert that we can further construct hybrid systems useful in engineering by combining sub-linear systems with linear systems, and as an example, we show the construction of a divergence-free electrodynamics. Since the energy of photon fields in engineering is tending upward, it would be desirable for us to get rid of the divergence difficulties encountered in the conventional high energy electrodynamics. The most important result is the recognition that Nature herself has a hybrid system composed of sub-linear photon fields and linear electron fields. Mathematically, our electrodynamics is formulated by only one point correction (the insertion of tanh into the electromagnetic energy density) in the conventional electrodynamics of photons and electrons (including positrons).

Moment matrix analysis (MMA) that can derive statistical properties of non-linear equations is presented in this paper. First, non-linear stochastic differential, or difference, equations are approximately expressed by simultaneous linear equations of moments defined at discrete events. Next, by eliminating higher order moments, the simultaneous linear equations are reduced to a linear vector equation of their coefficient matrix and a moment vector comprised of the moments of the system state. By computing the eigenvectors and eigenvalues of the coefficient matrix, we can analyze the moments, transient response, and spectrum of the system state. The behavior of Internet traffic was evaluated by using MMA and computer simulation, and it is shown that MMA is effective for evaluating simultaneous non-linear stochastic differential equations.

This paper deals with an on-line identification method based on a radial basis function (RBF) network model for continuous-time nonlinear systems. The nonlinear term of the objective system is represented by the RBF network. In order to track the time-varying system parameters and nonlinear term, the recursive least-squares (RLS) method is combined in a bootstrap manner with the genetic algorithm (GA). The centers of the RBF are coded into binary bit strings and searched by the GA, while the system parameters of the linear terms and the weighting parameters of the RBF are updated by the RLS method. Numerical experiments are carried out to demonstrate the effectiveness of the proposed method.

Dynamic non-linearities are of more importance in highly-linear high-speed applications such as software radios. In this paper, a fully-analytical approach to estimate the statistics of dynamic non-linearity parameters of pipeline analog-to-digital converters (ADCs) in the presence of circuit non-idealities is presented. These imperfections include the capacitor mismatches and the non-idealities in the operational amplifiers (op-amps). The most two important ADC dynamic non-linearity parameters, the spurious-free dynamic range (SFDR) and the signal-to-noise-and-distortion ratio (SNDR) are quantified here and closed-form formulas are presented. These formulas are useful for design automation as well as hand calculations of highly-linear pipeline ADCs. Behavioral simulations are presented to show the accuracy of the proposed equations.

In this paper, we propose a fast signature scheme which realizes short transmissions and minimal on-line computation. Our scheme requires a modular exponentiation as preprocessing (i.e., off-line computation). However, we need to acknowledge the existance of the following remarkable properties: neither multiplication nor modular reduction is used in the actual signature generation (i.e., on-line computation). Our scheme requires only two operations: hashing and addition. Although some fast signature schemes with small on-line computation have been proposed so far, those schemes require multiplication or modular reduction in the on-line phase. This leads to a large amount of work compared to that of addition. As far as we know, this is the first approach to obtain the fast signature without those two calculus methods.

This paper presents a novel digit-level algorithm for motion estimation (ME) and its hardware implementations. It uses the most-significant-digit-first (MSD-first) processing and on-line arithmetic ME components. A dedicated array architecture is also proposed for applications with high-throughput ME. Various fast search algorithms were presented in literatures to reduce the complexity but sacrifice the motion vector (MV) quality. Our MSD-first ME decomposes the summation of absolute differences (SAD) and comparison operations to digit level with MSD-plane first. These comparisons are interleaved into SADs to distinguish the MV as soon as possible. The algorithm precisely extracts the impossible candidates and removes their rest operations. It saves 47.4 % to 64.3 % of SAD computations in full search block matching (FSBM) ME. In the past, the high implementation cost of redundant number system prevented the practical use of on-line arithmetic. Besides, the redundant SAD removal results in irregular data flow in system-level integration. All these problems are solved by our novel architecture design. In this paper, we propose novel architecture designs to solve these problems. Besides, the architecture requires only one memory access per pixel to lower memory bandwidth by extensive data parallelism and a particular memory addressing while keeping the controller simple. A 4 4 array processor is implemented in 0.35 µm 1P4M CMOS cell library, with 2.84 ns cycle time and 1510 gates. It can support 83 M FSBM operations per second. After normalization, our implementation can support 2.67 times SAD operations per unit area (estimated in gate count) of the conventional two's complement ones. MSD-first ME can realize with other ME algorithms to improve the performance as well.

In this paper, we propose an on-line writer recognition method for Thai numeral. A handwriting process is characterized by a change of numeral's shape, which is represented by two features, a displacement of pen-point position and an area of triangle determined from the two adjacent points of pen-point position and the origin. First, the above two features are expanded into Fourier series. Secondly, in order to describe feature of handwriting, FIR (Finite impulse response) system having the above Fourier coefficients as input and output of the system is introduced. The impulse response of the FIR system is used as the feature of handwriting. Furthermore, K-L expansion of the obtained impulse response is used to recognize writer. Writer recognition experiments are performed by using 3,770 data collected by 54 Thai writers for one year. The average of Type I (false rejection) error rate and Type II (false acceptance) error rate were 2.16% and 1.12%, respectively.