In literature, many methods have been presented for enumerating binary trees (full binary trees) and regular k-ary trees, while no one for enumerating arbitrary trees or arbitrary k-ary trees. It is proposed in 1997 using a context-free grammar GBT (GFBT) to code binary trees (full binary trees) for enumerating them. In this paper, we use another grammar GT (GTk) to code arbitrary trees (arbitrary k-ary trees) for enumerating them. The properties of words of Ln(GT) (Ln(GTk)) are discussed in depth, including necessary and sufficient conditions for a word, prefix and suffix of Ln(GT) (Ln(GTk)), and efficient algorithms are given and analyzed for the enumeration of words of Ln(GT) (Ln(GTk)).

This paper presents the several bifurcation phenomena generated in nonlinear three-phase circuit with symmetry. The circuit consists of delta-connected nonlinear inductors, capacitors and three-phase symmetrical voltage sources. Particular attention is paid to the subharmonic oscillations of order 1/2. We analyze the bifurcations of the oscillations from both theoretical and experimental points. As a tool of analysis, we use the homotopy method. Additionally, by comparing with single-phase and single-phase-like circuits, the special feature of the three-phase circuit is revealed.

A new asynchronous transfer mode adaptation layer (AAL), called AAL2, is being designed mainly for low-bit-rate voice traffic, and nodes that can assemble and disassemble AAL2 cells are being developed to make AAL2 usage efficient. This paper investigates the delay and performance of AAL2 nodes by an analytical method. Then, using the results, it analyzes a network using AAL2 nodes and shows the bandwidth reduction achieved by using AAL2 switching nodes as transit nodes.

This paper proposes an automatic method for reconstructing a realistic 3D facial image from CT (computer tomography) and three color photographs: front, left and right views, which can be linked easily with the underlying bone and soft tissue models. This work is the first part of our final goal, "the prediction of patient's facial appearance after cancer surgery" such as removal of a part of bone or soft tissues. The 3D facial surface derived from CT by the marching cubes algorithm is obviously colorless. Our task is to add the color texture of the same patient actually taken with a digital camera to the colorless 3D surface. To do this it needs an accurate registration between the 3D facial image and the color photograph. Our approach is to set up a virtual camera around the 3D facial surface to register the virtual camera images with the corresponding color photographs by automatically adjusting seven parameters of the virtual camera. The camera parameters consists of three rotations, three translations and one scale factor. The registration algorithm has been developed based upon Besl and McKay's iterative closest point (ICP) algorithm.

In multi-media systems, the type of interactive communication channels is found almost everywhere and plays an important role, as well as the type of unilateral communication channels. In this report, we shall construct a fluctuation theory based on the concept of set-valued mappings, suitable for evaluation, control and operation of interactive communication channels in multi-media systems, complicated and diversified on large scales. Fundamental conditions for availability of such channels are clarified in a form of fixed point theorem for system of set-valued mappings.

In this paper we propose a heterogeneous agents model that represents speculative dynamics by using the synergetic approach. We consider the markets for three securities (a stock, a bond, and a foreign currency). Each market consists of two typical types of investors: fundamentalists and bandwagon traders. We show the characteristic patterns of speculative prices (speculative bubbles and speculative chaos) which are generated by trading between the fundamentalists and bandwagon traders.

Comparison of TDM and WDM for backbone ring network application is discussed from the perspective of system economizing. A critical advantage that WDM can provide is the optical pass-through function at a node having a relatively small drop and insert bandwidth. Circumstances where WDM is more advantageous than TDM are frequent especially in center-node type ring networks.

In this paper, performance degradation of satellite broadcasting receiving antenna systems due to weather conditions is examined by measuring their G/T continuously. We show that an offset parabolic reflector antenna of smaller aperture tends to be less affected by weather conditions.

We consider a circuit composed of linear capacitors, nonlinear resistors, and dc voltage sources and show the possibility that the total energy dissipated at resistors in the above circuit is smaller than the energy stored at capacitors. Linear passive circuits cannot possess such a property.

Clustering is almost essential in improving the performance of iterative partitioning algorithms. In this paper, we present a clustering algorithm based on the following observation: if a group of cells is assigned to the same partition in numerous local optimum solutions, it is desirable to merge the group into a cluster. The proposed algorithm finds such a group of cells from randomly generated local optimum solutions and merges it into a cluster. We implemented a multilevel bipartitioning algorithm (MBP) based on the proposed clustering algorithm. For MCNC benchmark netlists, MBP improves the total average cut size by 9% and the total best cut size by 3-4%, compared with the previous state-of-the-art partitioners.

When we have a singular Cab curve with many rational points, we had better to construct linear codes on its normalization rather than the original curve. The only obstacle to construct linear codes on the normalization is finding a basis of L( Q) having pairwise distinct pole orders at Q, where Q is the unique place of the Cab curve at infinity. We present an algorithm finding such a basis from defining equations of the normalization of the original Cab curve.

This paper proposes non-volatile analog memory circuits using pulse-width modulation (PWM) methods. The conventional analog memory using floating gate device has a trade-off between programming speed and precision because of the constant width of write pulses. The proposed circuits attain high programming speed with high precision by using PWM write pulses. Three circuits are proposed and their performance is evaluated using SPICE simulation. The simulation results show that fast programming time less than 20 µs, high updating resolution of 11 bits, and high precision more than 7 bits are achieved.

This paper shows the design of multi-stage fuzzy inference system with smaller number of rules based upon the optimization of rules by using the genetic algorithm. Since the number of rules of fuzzy inference system increases exponentially in proportion to the number of input variables powered by the number of membership function, it is preferred to divide the inference system into several stages (multi-stage fuzzy inference system) and decrease the number of rules compared to the single stage system. In each stage of inference only a portion of input variables are used as the input, and the output of the stage is treated as an input to the next stage. If we use the simplified inference scheme and assume the shape of membership function is given, the same backpropagation algorithm is available to optimize the weight of each rule as is usually used in the single stage inference system. On the other hand, the shape of the membership function is optimized by using the GA (genetic algorithm) where the characteristics of the membership function is represented as a set of string to which the crossover and mutation operation is applied. By combining the backpropagation algorithm and the GA, we have a comprehensive optimization scheme of learning for the multi-stage fuzzy inference system. The inference system is applied to the automatic bond rating based upon the financial ratios obtained from the financial statement by using the prescribed evaluation of rating published by the rating institution. As a result, we have similar performance of the multi-stage fuzzy inference system as the single stage system with remarkably smaller number of rules.

This paper presents two competitive learning methods with the objective of avoiding the initial dependency of weight (reference) vectors. The first is termed the refractory and competitive learning algorithm. The algorithm has a refractory period: Once the cell has fired, a winner unit corresponding to the cell is not selected until a certain amount of time has passed. Thus, a specific unit does not become a winner in the early stage of processing. The second is termed the creative and competitive learning algorithm. The algorithm is presented as follows: First, only one output unit is prepared at the initial stage, and a weight vector according to the unit is updated under the competitive learning. Next, output units are created sequentially to a prespecified number based on the criterion of the partition error, and competitive learning is carried out until the ternimation condition is satisfied. Finally, we discuss algorithms which have little dependence on the initial values and compare them with the proposed algorithms. Experimental results are presented in order to show that the proposed methods are effective in the case of average distortion.

Feature selection is an integral part of any pattern recognition system. Removal of redundant features improves the efficiency of a classifier as well as cut down the cost of future feature extraction. Recently neural network classifiers have become extremely popular compared to their counterparts from statistical theory. Some works on the use of artificial neural network as a feature selector have already been reported. In this work a simple feature selection algorithm has been proposed in which a fractal neural network, a modified version of multilayer perceptron, has been used as a feature selector. Experiments have been done with IRIS and SONAR data set by simulation. Results suggest that the algorithm with the fractal network architecture works well for removal of redundant informations as tested by classification rate. The fractal neural network takes lesser training time than the conventional multilayer perceptron for its lower connectivity while its performance is comparable to the multilayer perceptron. The ease of hardware implementation is also an attractive point in designing feature selector with fractal neural network.

This paper explores a possibility of constructing massively parallel molecular computing systems using molecular electronic devices called enzyme transistors. The enzyme transistor is, in a sense, an artificial catalyst which selects a specific substrate molecule and transforms it into a specific product. Using this primitive function, various active continuous media for signal transfer/processing can be realized. Prominent examples discussed in this paper are: (i) Turing pattern formation and (ii) excitable wave propagation in a two-dimensional enzyme transistor array. This paper demonstrates the potential of enzyme transistors for creating reaction-diffusion dynamics that performs useful computations in a massively parallel fashion.

A new vector-matching circuit technology has been developed aiming at compact implementation of maximum likelihood search engine for neuron-MOS associative processor. The new matching cell developed in this work possessed the template information in the form of an analog mask ROM and calculates the absolute value of difference between the template vector and the input vector components. The analog-mask ROM merged matching cell is composed of only five transistors to be compared with our earlier-version memory separated matching cell of 13 transistors. In addition, the undesirable cell-to-cell data interference through the common floating node ("boot-strap effect") has been eliminated without using power-consuming current source loads in source followers. As a result, dc-current-free matching cell operation has been established, making it possible to build a low-power, high-density search engine. Test circuits were fabricated by a 0.8-µm double-polysilicon double-metal n-well CMOS process, and the circuit operation has been experimentally verified.

In digital modulation for mobile radio telephone services frequency modulation with continuous phase with small modulation indices (MSK/GMSK) is sometimes used. Extension of the synchronization subsystems' pulling band in a coherent receiver and reducing synchronization delay is important for the mobile communication. At this moment there are only two possible synchronization schemes for the coherent MSK/GMSK receiver: Costas and de Buda's. This paper presents a new method (a possible alternative to both of them) where the frequency discriminator with decoupled carrier and bit synchronizing subsystem are combined to handle the task. For comparison, this paper also describes performances of the Costas carrier recovery scheme, which is widely employed for MSK/GMSK coherent demodulation. Discrimination and fluctuation characteristics for frequency, phase, and symbol delay synchronization subsystems are shown and the BER degradation from the conventional Costas scheme is calculated. This paper demonstrates with simulation results that the proposed scheme improves RF carrier acquisition performances, and at the same time, for large signal-to-noise ratios (SNR's) provides similar or better tracking performances than the Costas one. While limited to higher SNR ratios, the proposed synchronization scheme is suitable for many applications and can be implemented with simpler circuitry, well suited to integrated circuit implementation.

In this paper, we present the theoretical development to stabilize a class of uncertain time-delay system. The system under consideration is described in state space model containing distributed delay, uncertain parameters and disturbance. The main idea is to transform the system state into an equivalent one, which is easier to analyze its behavior and stability. Then, a computational method of robust controller design is presented in two parts. The first part is based on solving a Riccati equation arising in the optimal control theory. In the second part, the finite dimensional Lyapunov min-max approach is employed to cope with the uncertainties. Finally, we show how the resulting control law ensures asymptotic stability of the overall system.

The current-voltage characteristics of a single electron transistor (SET) in the resonant transport mode are investigated. In the future when SET devices are applied to integrated electronics, the quantum effect will seriously modify their characteristics in ultra-small geometry. The current will be dominated by the resonant transport through narrow energy levels in the dot. The simple case of a two-level system is analyzed and the transport mechanism is clarified. The transport property at low temperatures (higher than the Kondo temperature) in the low tunneling rate limit is discussed, and a current map where current values are classified in the gate bias-drain bias plane is provided. It was shown that the dynamic aspect of electron flow seriously influences the current value.