In this paper, a clustering-based method is proposed for automatically constructing a multi-input Takagi-Sugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated by the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to provide a systematic procedure to partition the input space so that the number of fuzzy rules and the shapes of fuzzy sets in the premise part are determined from the given input-output data. In the parameter identification step, the recursive least-squares algorithm is applied to choose the parameter values in the consequent part from the given input-output data. Finally, two examples are used to illustrate the effectiveness of the proposed method.

This paper considers the problem of generating various calligraphy from some sample fonts. Our method is based on the deformable contour model g-snake. By representing the outline of each stroke of a character with a g-snake, we cast the generation problem into global and local deformation of g-snake under different control parameters, where the local deformation obeys the energy minimization principle of regularization technique. The base values of the control parameters are learned from given sample fonts. The experimental results on alphabet and Japanese characters Hiragana show such processing as a reasonable method for generating calligraphy.

This paper discusses the classification of targets buried in the underground by radar polarimetry. The subsurface radar is used for the detection of objects buried beneath the ground surface, such as gas pipes, cables and cavities, or in archeological exploration operation. In addition to target echo, the subsurface radar receives various other echoes, because the underground is inhomogeneous medium. Therefore, the subsurface radar needs to distinguish these echoes. In order to enhance the discrimination capability, we first applied the polarization anisotropy coefficient to distinguish echoes from isotropic targets (plate, sphere) versus anisotropic targets (wire, pipe). It is straightforward to find the man-made target buried in the underground using the polarization anisotropy coefficient. Second, we tried to classify targets using the polarimetric signature approach, in which the characteristic polarization state provides the orientation angle of an anisotropic target. All of these values contribute to the classification of a target. Field experiments using an ultra-wideband (250 MHz to 1 GHz) FM-CW polarimetric radar system were carried out to show the usefulness of radar polarimetry. In this paper, several detection and classification results are demonstrated. It is shown that these techniques improve the detection capability of buried target considerably.

We propose a motion estimation algorithm using less gray level images, which are composed of bits pixels lower than 8 bits pixels. Threshold values for generating low bits pixels from 8 bits pixels are simply determined as median values of pixels in a macro block. The proposed algorithm reduces the computational complexity of motion estimation at less expense of video quality. Moreover, median cut quantization can be applied to multilevel images and combined with a lot of fast algorithms to obtain more effective algorithms.

In this paper, by making good use of the parallel-transit-evaluation algorithm and sparsity of the connection between neurons, a pipeline structure is successfully introduced to the sequential Boltzmann machine processor. The novel structure speeds up nine times faster than the previous one, with only the 12% rise in hardware resources under 10,000 neurons. The performance is confirmed by designing it using 1.2 µm CMOS process standard cells and analyzing the probability of state-change.

In this paper, a new digital chaos circuit which can generate multiple-scroll strange attractors is proposed. Being based on the piecewise-linear function which is determined by on-chip supervised learning, the proposed digital chaos circuit can generate multiple-scroll strange attractors. Hence, the proposed circuit can exhibit various bifurcation phenomena. By numerical simulations, the learning dynamics and the quasi-chaos generation of the proposed digital chaos circuit are analyzed in detail. Furthermore, as a design example of the integrated digital chaos circuit, the proposed circuit realizing the nonlinear function with five breakpoints is implemented onto the FPGA (Field Programmable Gate Array). The synthesized FPGA circuit which can generate n-scroll strange attractors (n=1, 2, 4) showed that the proposed circuit is implementable onto a single FPGA except for the SRAM.

In this paper, we introduce a lower bound for the generalized Hamming weights, which is applicable to arbitrary linear code, in terms of the notion of well-behaving. We also show that any [n,k] linear code C over a finite field F is the t-th rank MDS for t such that g(C)+1 t k where g(C) is easily calculated from the basis of Fn so chosen that whose first n-k elements generate C. Finally, we apply our result to Reed-Solomon, Reed-Muller and algebraic geometry codes on Cab, and determine g(C) for each code.

In this paper, a novel variable-rate vector quantizer (VQ) design algorithm using fuzzy clustering technique is presented. The algorithm, termed fuzzy entropy-constrained VQ (FECVQ) design algorithm, has a better rate-distortion performance than that of the usual entropy-constrained VQ (ECVQ) algorithm for variable-rate VQ design. When performing the fuzzy clustering, the FECVQ algorithm considers both the usual squared-distance measure, and the length of channel index associated with each codeword so that the average rate of the VQ can be controlled. In addition, the membership function for achieving the optimal clustering for the design of FECVQ are derived. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable-rate VQs.

We introduce an extended EZW coder that uses flexible zerotree coding of wavelet coefficients. A flexible parent-child relationship is defined so as to exploit spatial dependencies within a subband as well as hierarchical dependencies among multi-scale subbands. The new relationship is based on a particular statistics that a large coefficient is more likely to have large coefficients in its neighborhood in terms of space and scale. In the flexible relationship, a parent coefficient in a subband relates to four child coefficients in the next finer subband in the same orientation. If each of the children is larger than a given threshold, the parent extends its parentship to the neighbors close to its conventional children. A probing bit is introduced to indicate whether a significant parent has significant children to be scanned. This enables us to avoid excessive scan of insignificant coefficients. Also, produced symbols are re-symbolized into simple variable-length binary codes to remove some redundancy according to a pre-defined rule. As a result, the wavelet coefficients can be described with a small number of binary symbols. This binary symbol stream gives a competitive performance without an additional entropy coding and thus a fast encoding/decoding is possible. Moreover, the binary symbols can be more compressed by an adaptive arithmetic coding. Our experimental results are given in both binary-coded mode and arithmetic-coded mode. Also, these results are compared with those of the EZW coder.

The full-band Monte Carlo technique is currently the most accurate device simulation method, but its usefulness is limited because it is very CPU intensive. This work describes efficient algorithms in detail, which raise the efficiency of the full-band Monte Carlo method to a level where it becomes applicable in the device design process beyond exemplary simulations. The k-space is discretized with a nonuniform tetrahedral grid, which minimizes the discretization error of the linear energy interpolation and memory requirements. A consistent discretization of the inverse mass tensor is utilized to formulate efficient transport parameter estimators. Particle scattering is modeled in such a way that a very fast rejection technique can be used for the generation of the final state eliminating the main cause of the inefficiency of full-band Monte Carlo simulations. The developed full-band Monte Carlo simulator is highly efficient. For example, in conjunction with the nonself-consistent simulation technique CPU times of a few CPU minutes per bias point are achieved for substrate current calculations. Self-consistent calculations of the drain current of a 60nm-NMOSFET take about a few CPU hours demonstrating the feasibility of full-band Monte Carlo simulations.

This paper presents a method of calculating an interval including a bifurcation point. Turning points, simple bifurcation points, symmetry breaking bifurcation points and hysteresis points are calculated with guaranteed accuracy by the extended systems for them and by the Krawczyk-based interval validation method. Taking several examples, the results of validation are also presented.

A new concept of "an imperfect singular solution" is defined as an approximate solution which becomes a singular solution by adding a suitable small perturbation to the original equations. A numerical method is presented for proving the existence of imperfect singular solutions of nonlinear equations with guaranteed accuracy. A few numerical examples are also presented for illustration.

This paper reports computational results of a new approach of analyzing network reliability against probabilistic link failures. This problem is hard to solve exactly when it is large-scale, which is shown from complexity theory, but the approach enables us to analyze networks of moderate size, as demonstrated by our experimental results. Furthermore, this approach yields a polynomial-time algorithm for complete graphs, whose reliability provides a natural upper bound for simple networks, and also leads to an efficient algorithm for computing the dominant part of the reliability function when the failure probability is sufficiently small. Computational results for these cases are also reported. This approach thus establishes a fundamental technology of analyzing network reliability in practice.

Regular ternary logic functions are one of the most useful special classes of Kleenean functions, and a lot of research has been done on them. However, there has been little work done on incompletely specified regular ternary logic functions. This paper describes the following points: (1) Minimization of incompletely specified regular ternary logic functions. (2) A new definition of incompletely specified fuzzy switching functions and their minimization. (Concretely speaking, minimal disjunctive forms of incompletely specified fuzzy switching functions are represented in formulas of regular ternary logic functions. ) (3) Their application to fuzzy logic circuits such as fuzzy PLAs of AND-OR type.

We propose two fault-tolerant broadcasting schemes in star graphs. One of the schemes can tolerate up to n2 faults of the crash type in the n-star graph. The other scheme can tolerate up to (n3d1)/2 faults of the Byzantine type in the n-star graph, where d is the smallest positive integer satisfying nd!. Each of the schemes is designed for the single-port mode, and it completes the broadcasting in O(n log n) time. These schemes are time optimal. For the former scheme we analyze the reliability in the case where faults of the crash type are randomly distributed. It can tolerate (n!)α faults randomly distributed in the n-star graph with a high probability, where α is any constant less than 1.

Cerebellar Model Articulation Controller (CMAC) has been proposed as one of artificial neural networks. This paper describes a design scheme of intelligent control system consists of some CMACs. Each of CMACs is trained for the specified reference signal. A new CMAC is generated for unspecified reference signals, and the CMAC whose reference signal is nearest for the new reference signal, is eliminated. Therefore, since the reference signals are removed from the input signals of the CMAC, the proposed intelligent controller can be designed with fairly small memories.

Technologies used to characterize and compensate nonlinearities in microwave power amplifiers are discussed. First, a complex power series representation that allows both amplitude and phase nonlinearities to be dealt with simultaneously is proposed, and in order to estimate the 3rd-order complex coefficient phase of practical amplifiers, two kinds of experimental measurement methods are proposed. Next, the fundamental circuit configuration of IF cuber predistortion linearizer that compensates 3rd-order intermodulation distortion is derived from a nonlinear analysis using complex power series representation. Two practical cuber predistorters for the 6-GHz TWTA and the 800-MHz FET-PA are demonstrated. Moreover, the unique nonlinear compensation technology of side-band inversion is introduced for microwave relay system using TWTAs. Finally, the self-adjusting feed-forward (SAFF)-PA developed for digital cellular base stations is reviewed.

This paper describes amplification with improved linearity by employing a linearizing circuit in an input circuit of an internally-matched Ku-band high power amplifier. The linearizing circuit is composed of series L, C, R and an FET with grounded source and drain, and is connected between the input signal line and ground. This linearizing circuit was applied to a Ku-band 10 W output power amplifier utilizing a 25.2 mm gate-width double-doped Heterojunction FET. The power amplifier demonstrated a 8 dB reduction of the third-order intermodulation at about 6 dB output power backoff point from the 2 dB output compression point.

We propose an H-plane manifold-type triplexer with closely arranged junctions. Broadband characteristics for each bands are obtained by arranging filters closely near the end of the common waveguide. Three fundamental and sufficient parameters are introduced for numerical optimizations to determine the configuration of the broadband triplexer. The configuration including closely arranged junctions requires an generalized scattering matrix (GS matrix) of an asymmetric cross junction to simulate and design. We expand the mode matching technique (MMT) to be able to analyze this kind of discontinuities by joining two asymmetric steps discontinuities to a symmetric cross junction. This is suitable expressions for numerical calculations. The characteristics of the whole triplexer are obtained by cascading GS matrices of the corresponding discontinuities. The experimental results of the fabricated triplexer were compared with the simulated data, and the results agree well with the simulated one. The characteristics of the fabricated triplexer satisfy the request of the broad band operation and high power-handling capability.

This paper proposes a thresholding based segmentation method aided by Kleene Algebra. For a given image including some regions of interest (ROIs for short) with the coherent intensity level, assume that we can segment each ROI on applying thresholding technique. Three segmented states are then derived for every ROI: Shortage denoted by logic value 0, Correct denoted by 1 and Excess denoted by 2. The segmented states for every ROI in the image can be then expressed on a ternary logic system. Our goal is then set to find "Correct (1)" state for every ROI. First, unate function, which is a model of Kleene Algebra, based procedure is proposed. However, this method is not complete for some cases, that is, correctly segmented ratio is about 70% for three and four ROI segmentation. For the failed cases, Brzozowski operations, which are defined on De Morgan algebra, can accommodate to completely find all "Correct" states. Finally, we apply these procedures to segmentation problems of a human brain MR image and a foot CT image. As the result, we can find all "1" states for the ROIs, i. e. , we can correctly segment the ROIs.