Simplification orderings, like the recursive path ordering and the improved recursive decomposition ordering, are widely used for proving the termination property of term rewriting systems. The improved recursive decomposition ordering is known as the most powerful simplification ordering. Recently Jouannaud and Rubio extended the recursive path ordering to higher-order rewrite systems by introducing an ordering on type structure. In this paper we extend the improved recursive decomposition ordering for proving termination of higher-order rewrite systems. The key idea of our ordering is a new concept of pseudo-terminal occurrences.

Recently, a trellis-based recursive maximum likelihood decoding (RMLD) algorithm has been proposed for decoding binary linear block codes. This RMLD algorithm is computationally more efficient than the Viterbi decoding algorithm. However, the computational complexity of the RMLD algorithm depends on the sectionalization of a code trellis. In general, minimization of the computational complexity results in non-uniform sectionalization of a code trellis. From implementation point of view, uniform sectionalization of a code trellis and regularity among the trellis sections are desirable. In this paper, we apply the RMLD algorithm to a class of codes which are transitive invariant. This class includes Reed-Muller (RM) codes, the extended and permuted BCH (EBCH) codes and their subcodes. For this class of codes, the binary uniform sectionalization of a code trellis results in the following regular structure. At each step of decoding recursion, the metric table construction procedure is applied uniformly to all the sections and the size and structure of each metric table are the same. This simplifies the implementation of the RMLD algorithm. Furthermore, for all RM codes of lengths 64 and 128 and EBCH codes of lengths 64 and 128 with relatively low rate, the computational complexity of the RMLD algorithm based on the binary uniform sectionalization of a code trellis is almost the same as that based on an optimum sectionalization of a code trellis.

Conventional approaches to neural network training do not consider possibility of selecting training samples dynamically during the learning phase. Neural network is simply presented with the complete training set at each iteration of the learning. The learning can then become very costly for large data sets. Huge redundancy of data samples may lead to the ill-conditioned training problem. Ill-conditioning during the training causes rank-deficiencies of error and Jacobean matrices, which results in slower convergence speed, or in the worst case, the failure of the algorithm to progress. Rank-deficiencies of essential matrices can be avoided by an appropriate selection of training exemplars at each iteration of training. This article presents underlying theoretical grounds for dynamic sample selection (DSS), that is mechanism enabling to select a subset of training set at each iteration. Theoretical material is first presented for general objective functions, and then for the objective functions satisfying the Lipschitz continuity condition. Furthermore, implementation specifics of DSS to first order line search techniques are theoretically described.

In this paper, experimental results of evaluating dialogue strategies of confirmation with a noisy channel are presented. First, the types of errors in task-oriented dialogues are investigated and classified as communication, dialogue, knowledge, problem solving, or objective errors. Since the errors are of different levels, the methods for recovering from errors must be examined separately. We have investigated that the dialogue and knowledge errors generated by communication errors can be recovered through system confirmation with the user. In addition, we examined that the manner in which a system initiates dialogue, namely, dialogue strategies, might influence the cooperativity of their interactions depending on the frequency of confirmations and the amount of information conveyed. Furthermore, the choice of dialogue strategies will be influenced by the rate of occurrence of communication errors in a communication channel and related to the properties of the task, for example, the difficulty in achieving a goal or the frequency of the movement of initiatives. To verify these hypotheses, we prepared a testbed task, the Group Scheduling Task, and examined it through a computer-to-computer dialogue simulation in which one system took the part of a scheduling system and the other system acted as a user. In this simulation, erroneous input for the scheduling system was also developed. The user system was designed to act randomly so that it could simulate a real human user, while the scheduling system was devised to strictly follow a particular dialogue strategy of confirmation. The experimental results showed that a certain amount of confirmation was required to overcome errors when the rate of occurrence of communication errors was high, but that excessive confirmation did not serve to resolve errors, depending on the task involved.

We propose an information integration architecture for a man-machine interface to construct a new agent-based Computer Supported Cooperative Work (CSCW) system. The system acts as a clerk in cooperative work giving users the advantage of using cooperative work space. The system allows users to do their work in the style of an ordinary meeting because spontaneous expressions of speech and gestures by users are detected by sensors so that they can be integrated with a task model at several levels to create suitable responses in a man-machine interface. As a result, users can dedicate themselves to mutually understand other meeting members with no awareness of direction to the CSCW system. In this paper, we describe the whole system and its information integration architecture for the man-machine interface including, the principle of functions, the current status of the system and future directions.

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.

In this paper we propose a method to aid a visually impaired person in the operation of a computer running a graphical user interface (GUI). It is based on image processing techniques, using images taken by a color camera placed over a Braille display. The shape of the user's hand is extracted from the image by analyzing the hue and saturation histograms. The orientation of the hand, given by an angle θ with the vertical axis, is calculated based on central moments. The image of the hand is then rotated to a normalized position. The number of pixels in each column of the normalized image is counted, and the result is put in a histogram. By analyzing the coefficient of asymmetry of this histogram, it can be determined whether the thumb is positioned along the pointing finger, or whether it is far from the other fingers. These two positions define two states that correspond to a mouse button up or down. In this way, by rotating the hand and moving the thumb, we can emulate the acts of moving a scroll bar and depressing a mouse button, respectively. These operations can be used to perform tasks in a GUI, such as cut-and-paste, for example. Experimental results show that this method is fast and efficient for the proposed application.

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.

In this study, a coupled chaotic circuits network is realized by real circuit elements. By using a simple circuit converting generating spatial patterns to digital signal, irregular self-switching phenomenon of the appearing patterns can be observed as real physical phenomenon.

This paper proposes a dual port color palette SRAM using a single bit line cell. Since the single bit line cell consists of fewer bit lines and transistors than standard dual port cells, it is able to reduce the area. However, the cell has had a problem in writing a high level. The port swap architecture solves the problem without any special mechanism such as a boot strap. In the architecture, each of two bit lines is assigned to the read/write MPU port and the read only pixel port, respectively. When writing a low level, the MPU port uses pre-assigned bit line. On the other hand, when writing a high level, the MPU port uses the bit line assigned to the pixel port by a swap operation. During the swapping, the pixel port continues the read operation by using the bit line assigned to the MPU port. A color palette using this architecture is fabricated with a 0. 5 µm CMOS process technology. The memory cell size reduces by up to 43% compared with standard dual port cells. The color palette is able to supply the pixel data at 300 MHz at the supply voltage of 3.3 V. This speed is enough to support the practical highest resolution monitors in the world.

In the design of nonlinear reliable controllers, one major issue is to solve for the solutions of the Hamilton-Jacobi inequality. In general, it is hard to obtain a closed form solutions due to the nonlinear nature of the inequality. In this paper, we seek for the existence conditions of quadratic type positive semidefinite solutions of Hamilton-Jacobi inequality. This is achieved by taking Taylor's series expansion of system dynamics and investigating the negative definiteness of the associated Hamilton up to fourth order. An algorithm is proposed to seek for possible solutions. The candidate of solution is firstly determined from the associated algebraic Riccati inequality. The solution is then obtained from the candidate which makes the truncated fourth order polynomial of the inequality to be locally negative definite. Existence conditions of the solution are explicitly attained for the cases of which system linearization possesses one uncontrollable zero eigenvalue and a pair of pure imaginary uncontrollable eigenvalues. An example is given to demonstrate the application to reliable control design problem.

In this paper, we propose an adaptive lattice-transversal joint (LTJ) filter structure that is quite suitable for the practical implementation of the acoustic echo canceller. The structure maintains fast convergence of the lattice structure and low computational complexity of the transversal structure simultaneously. It is particularly more efficient in memory usage than any other existing fast-convergent algorithm for the acoustic echo cancellation.

Computational expensiveness of the training techniques, due to the extensiveness of the data set, is among the most important factors in machine learning and neural networks. Oversized data set may cause rank-deficiencies of Jacobean matrix which plays essential role in training techniques. Then the training becomes not only computationally expensive but also ineffective. In [1] the authors introduced the theoretical grounds for dynamic sample selection having a potential of eliminating rank-deficiencies. This study addresses the implementation issues of the dynamic sample selection based on the theoretical material presented in [1]. The authors propose a sample selection algorithm implementable into an arbitrary optimization technique. An ability of the algorithm to select a proper set of samples at each iteration of the training has been observed to be very beneficial as indicated by several experiments. Recently proposed approaches to sample selection work reasonably well if pattern-weight ratio is close to 1. Small improvements can be detected also at the values of the pattern-weight ratio equal to 2 or 3. The dynamic sample selection approach, presented in this article, can increase the convergence speed of first order optimization techniques, used for training MLP networks, even at the value of the pattern-weight ratio (E-FP) as high as 15 and possibly even more.

In this paper we propose a total quality evaluation method in an ATM network-type remote conference system, and describe the results of evaluations of a proving system. The quality of a remote conference system depends on such various elements as video images, voice signals, and cost; but a total quality index may be regarded as the cost of a remote conference system compared with that of a conventional face-to-face conference. Here, however, the decline in communication quality arising from the remote locations of participants must be included in the evaluation. Moreover, the relative weightings of voice signals, video images of participants, and shared data will vary depending on the type of conference, and these factors must also be taken into account in evaluations. An actual conference systems were constructed for evaluation, and based on a MOS (Mean Opinion Score) of the quality elements, the total system quality was evaluated with reference to the proposed concepts. These results are also described in this paper.

The required building blocks of CMOS fuzzy chips capable of performing as adaptive fuzzy systems are described in this paper. The building blocks are designed with mixed-signal current-mode cells that contain low-resolution A/D and D/A converters based on current mirrors. These cells provide the chip with an analog-digital programming interface. They also perform as computing elements of the fuzzy inference engine that calculate the output signal in either analog or digital formats, thus easing communication of the chip with digital processing environments and analog actuators. Experimental results of a 9-rule prototype integrated in a 2. 4-µm CMOS process are included. It has a digital interface to program the antecedents and consequents and a mixed-signal output interface. The proposed design approach enables the CMOS realization of low-cost and high-inference fuzzy systems able to cope with complex processes through adaptation. This is illustrated with simulated results of an application to the on-line identification of a nonlinear dynamical plant.

In this paper, the performances of texture classification based on pyramidal and uniform decomposition are comparatively studied with and without feature selection. This comparison using the subband variance as feature explores the dependence among features. It is shown that the main problem when employing 2-D non-separable wavelet transforms for texture classification is the determination of the suitable features that yields the best classification results. A Max-Max algorithm which is a novel evaluation function based on genetic algorithms is presented to evaluate the classification performance of each subset of selected features. It is shown that the performance with feature selection in which only about half of features are selected is comparable to that without feature selection. Moreover, the discriminatory characteristics of texture spread more in low-pass bands and the features extracted from the pyramidal decomposition are more representative than those from the uniform decomposition. Experimental results have verified the selectivity of the proposed approach and its texture capturing characteristics.

An optical communications technology roadmap leading up to the second decade of the 21st century has been investigated to provide a future vision of the optoelectronic technology in 15 to 20 years. The process whereby technology may progress toward the realization of the vision is indicated. A transmission rate of 100 Mbps for homes and a rate of 5 Tbps for the backbone network will be required in the first decade of the 21 century. Two technology roadmaps for public and business communications networks are discussed. It is concluded both WDM and TDM technology will be required to realize such an ultra-high capacity transmission. Technical tasks for various optical devices are investigated in detail.

The Heart Rate Variability (HRV) analysis has become vigorous these days. One reason for this is that the HRV analysis investigates the dynamics of the autonomic nervous system activities which control the HRV. The Integral Pulse Frequency Modulation (IPFM) model is a pulse generating mechanism model in the nervous system, that is one of the models which connects the HRV to the autonomic nervous system activities. The IPFM model is a single frequency component model; however, the real HRV has multiple frequency components. Moreover, there are refractory periods after generating action potentials are initiated. Nevertheless, the IPFM model does not consider refractory periods. In order to make sure of the accuracy and the effectiveness of the integral function (IF) method applied to the real data, we consider the absolute refractory periods and two frequency components. In this investigation, the simulated HRV was made with a single and double frequency component using the IPFM model with and without absolute refractory periods. The original generating function of the IPFM model was demodulated by using the instantaneous heart rate tachogram. The power of the instantaneous pulse rate per minute was analyzed by the direct FFT method, the IF FFT method without the absolute refractory periods, and the IF FFT method with the absolute refractory periods. It was concluded that the IF FFT method can demodulate the original generating function accurately.

It becomes essential in practice to improve a processing rate and to divide an image into small segments adjusting a limited memory, because image filing systems handle large images up to A1 size. This paper proposes a new method of an automatic skew normalization, comprising a high-speed skew detection and a distortion-free dividing rotation. We have evaluated the proposed method from the viewpoints of the processing rate and the accuracy for typed documents. As results, the processing rate is 2. 9 times faster than that of a conventional method. A practical processing rate for A1 size documents can be achieved under the condition that the accuracy of a normalized angle is controlled within 0. 3 degrees. Especially, the rotation with dividing can have no error angle, even when the A1 size documents is divided into 200 segments, whereas the conventional method cause the error angle of 1. 68 degrees.

This paper proposes a new approach to recover the sign of local surface curvature of object from three shading images using neural network. The RBF (Radial Basis Function) neural network is used to learn the mapping of three image irradiances to the position on a sphere. Then, the learned neural network maps the image irradiances at the neighbor pixels of the test object taken from three illuminating directions of light sources onto the sphere images taken under the same illuminating condition. Using the property that basic six kinds of surface curvature has the different relative locations of the local five points mapped on the sphere, not only the Gaussian curvature but also the kind of curvature is directly recovered locally from the relation of the locations on the mapped points on the sphere without knowing the values of surface gradient for each point. Further, two step neural networks which combines the forward mapping and its inverse mapping one can be used to get the local confidence estimate for the obtained results. The entire approach is non-parametric, empirical in that no explicit assumptions are made about light source directions or surface reflectance. Results are demonstrated by the experiments for real images.