The most basic cross-talk minimization problem is to assign given n intervals to n parallel tracks where the cross-talk is defined between two intervals assigned to the adjacent tracks with the amount linear to parallel running length. This paper solves the problem for the case when any pair of intervals intersects and the objective is to minimize the sum of cross-talks. We begin the discussion with the fact that twice the sum of lengths of n/2 shortest intervals is a lower bound. Then an interval set that attains this lower bound is characterized with a simple assignment algorithm. Some additional considerations provide the minimum cross-talk for the other interval sets. The main procedure is to sort the intervals twice with respect to the length of left and right halves of intervals.

Related with accuracy, computational complexity and so on, quality of computing for the so-called homotopy method has been discussed recently. In this paper, we shall propose an estimation method with interval analysis of region in which unique solution path of the homotopy equation is guaranteed to exist, when it is applied to a certain class of uniquely solvable nonlinear equations. By the estimation, we can estimate the region a posteriori, and estimate a priori an upper bound of the region.

This letter presents a new algorithm for improving the Signal to Noise Ratio (SNR) of complex sinusoidal signals contaminated by additive Gaussian noises using sum of Higher-Order Statistics (HOS). We conduct some computer simulations to show that the proposed algorithm can improve the SNR more than 7 dB compared with the conventional coherent integration when the SNR of the input signal is -10 dB.

This paper describes methods of tracking of moving objects in a cluttered background by integrating optical flow, depth data, and/or uniform brightness regions. First, a basic method is introduced which extracts a region with uniform optical flow as the target region. Then an extended method is described in which optical flow and depth are fused. A target region is extracted by Baysian inference in term of optical flow, depth and the predicted target location. This method works only for textured objects because optical flow or depth are extracted for textured objects. In order to solve this problem, uniform regions in addition to the optical flow are used for tracking. Realtime human tracking is realized for real image sequences by using a real time processor with multiple DSPs.

Modeling error is the major concerning issue in the trajectory estimation. This paper formulates the dynamic model of a reentry vehicle in reentry phase for identification with an unmodeled acceleration input covering possible model errors. Moreover, this work presents a novel on-line estimation approach, adaptive filter, to identify the trajectory of a reentry vehicle from a single radar measured data. This proposed approach combines the extended Kalman filter and the recursive least-squares estimator of input with the hypothetical testing scheme. The recursive least-squares estimator is provided not only to extract the magnitude of the unmodeled input but to offer a testing criterion to detect the onset and presence of the input. Numerical simulation demonstrates the superior capabilities in accuracy and robustness of the proposed method. In real flight analysis, the adaptive filter also performs an excellent estimation and prediction performances. The recommended trajectory estimation method can support defense and tactical operations for anti-tactical ballistic missile warfare.

This paper describes an efficient simulation algorithm for the spatiotemporal pattern analysis of the continuous-time neural networks with the multivalued logic (multivalued continuous-time neural networks). The multivalued transfer function of neuron is approximated to the stepwise constant function which is constructed by the sum of the step functions with the different thresholds. By this approximation, the dynamics of the network can be formulated as a stepwise constant linear differential equation at each timestep and the optimal timestep for the numerical integration can be obtained analytically. Finally, it is shown that the proposed method is much faster than a variety of conventional simulators.

This paper presents Power-Pro architecture (Programmable Power Management Architecture), a novel processor architecture for power reduction. The Power-Pro architecture has two key functionalities: (i) Supply voltage and clock frequency of a microprocessor can be dynamically varied, and (ii) active datapath width can be dynamically adjusted to the precision of each operation. The most unique point of this architecture is that software programmers can directly specify the requirements of applications such as real-time constraints and precision of the operations. To make programmable power management possible, Power-Pro architecture equips special instructions. Programmers can vary the supply voltage, the clock frequency and the active datapath width dynamically by the instructions. Experimental results show that power consumption for a variety of applications are dramatically reduced by the Power-Pro architecture.

The naturalness of normal sustained vowels is considered to be attributable to the fluctuations observed in the steady part where speech signal is seemingly almost periodic. There always exist two kinds of involuntary fluctuations in the steady part of sustained vowels, even if the sustained vowels are phonated as steadily as possible. One is pitch period fluctuation and the other is waveform fluctuation. In this study, frequency analyses on these fluctuations were conducted in order to investigate their general characteristics. The results of the analyses suggested that the frequency characteristics of the fluctuations were possible to be approximated as 1/fβ-like, which is regarded as the specific feature of random fractal. Therefore, a procedure based on random fractal generation methods was proposed in order to produce these fluctuations for the improvement of the voice quality of synthesized sustained vowels. A series of psychoacoustic experiments was also conducted to evaluate the proposed technique. Experimental results indicated that the proposed technique was effective for synthesized sustained vowels to be perceived as human-like. Unlike the sustained vowels which were synthesized without pitch period fluctuation nor waveform fluctuation, the synthesized sustained vowels which contained the fluctuations were not perceived as buzzer-like, which is the major problem of the voice quality of synthesized sustained vowels. However, it was also found that both of the fluctuations were not always the acoustic cues for the naturalness of normal sustained vowels. The synthesized sustained vowels which contained the fluctuations whose frequency characteristics were the same as that of white noise were perceived as noise-like, which is not at all the voice quality of normal sustained vowels. The results of psychoacoustic experiments indicated that the frequency characteristics of the fluctuations, which are possible to be modeled as 1/fβ-like, were the significant factors for the naturalness of normal sustained vowels.

In this paper, we show that two-dimensional billiards with point interactions inside exhibit a chaotic nature in the microscopic world, although their classical counterpart is non-chaotic. After deriving the transition matrix of the system by using the self-adjoint extension theory of functional analysis, we deduce the general condition for the appearance of chaos. The prediction is confirmed by numerically examining the statistical properties of energy spectrum of rectangular billiards with multiple point interactions inside. The dependence of the level statistics on the strength as well as the number of the scatterers is displayed.

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, we present a hierarchical technique for simultaneous pin assignment and global routing during floorplanning based on the minimum cost maximum integer flow algorithm with several heuristic cost functions. Furthermore, our algorithm handles feedthrough pins and equi-potential pins taking into account global routes. Our algorithm allows various user specified constraints such as pre-specified pin positions, wiring paths, wiring widths and critical nets. Experimental results including Xerox floorplanning benchmark have shown the effectiveness of the heuristics.

The VF (Variable-to-Fixed length) arithmetic coding method combines the advantage of an ordinary stream arithmetic code with the simplicity of a block code. One of the advantages of VF codes is that the transmission errors or channel errors do not propagate infinitely and are restricted to the block in question. In this paper, we propose a modified type of non-proper VF arithmetic coding method that defines an input alphabet subset according to both the number of codewords in the current codeword set and input symbol probability and that splits the codeword set completely for a newly defined alphabet subset when the codeword set becomes smaller by each splitting. The proposed coding method carrys out independence of each codeword and guarantees that there is no collision while there is a waste of codeword(s) in conventional AB-coding due to collision. We examine the performance of the proposed method and compare it with that of other VF codes in terms of compression ratio and algorithmic complexity.

Adaptive estimation of nonstationary sinusoidal signals or quasi-periodic signals in additive noise is of essential importance in many diverse engineering fields, such as communications, biomedical engineering, power systems, pitch detection in transcription and so forth. So far, Kalman filtering based techniques, recursive least square (RLS), simplified RLS (SRLS) and LMS algorithms, for examples, have been developed for this purpose. This work presents in detail a performance analysis for the SRLS algorithm proposed recently in the literature, which is used to estimate an enhanced sinusoid. Its dynamic and tracking properties, noise and lag misadjustments are developed and discussed. It is found that the SRLS estimator is biased, and its misadjustments are functions of not only the noise variance but also, unpleasantly, of the signal parameters. Simulations demonstrate the validity of the analysis. Application of the SRLS to a real-life piano sound is also given to peek at its effectiveness.

Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.

We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.

We show that characteristic functions of elements of self-similar tilings can be used as scaling functions of multiresolution analysis of L2(Rn). This multiresolution analysis is a generalization of a self-affine tiling multiresolution analysis using a characteristic function of element of self-affine tiling as a scaling function. We give a method of constructing a wavelet basis which realizes such an MRA.

In this paper, we propose a new approach for describing image patterns. We integrate the concepts of multiscale image analysis, aura matrix (Gibbs random fields and cooccurrences related statistical model of texture analysis) to define image features, and to obtain the features having robustness with illumination variations and shading effects, we analyse images based on the Topographic Structure described by the Surface-Shape Operator, which describe gray-level image patterns in terms of 3D shapes instead of intensity values. Then, we illustrate usefulness of the proposed features with texture classifications. Results show that the proposed features extracted from multiscale images work much better than those from a single scale image, and confirm that the proposed features have robustness with illumination and shading variations. By comparisons with the MRSAR (Multiresolution Simultaneous Autoregressive) features using Mahalanobis distance and Euclidean distance, the proposed multiscale features give better performances for classifying the entire Brodatz textures: 112 categories, 2016 samples having various brightness in each category.

A fiber Bragg grating, which has periodical perturbation of the refractive index in the fiber core, acts as a wavelength selective reflection filter and steep optical spectrum can be realized by forming more than ten thousand of gratings along the fiber core. Owing to capability of making steep optical spectrum, fiber Bragg gratings has been expected to be introduced practical use as multiplexing or demultiplexing filters in dense WDM transmission systems. On the other hand, radiation mode loss, reflection side mode and temperature dependence of Bragg wavelength, should be improved to put the fiber Bragg grating to practical use in dense WDM transmission systems. In this paper, an optimum design and performance of the fiber Bragg grating for dense WDM systems are described. The photosensitive cladding fiber realized less than 0. 2 dB insertion loss at transmitted signal channels and less than 0. 1 dB splicing loss with standard single-mode fibers. An adequate apodization technique in the refractive index distribution suppressed reflection side modes. A temperature compensating package, which gives longitudinal strain with negative temperature dependence to a fiber Bragg grating, minimized temperature dependence of Bragg wavelength less than 0. 001 nm/. Thermal decay of Bragg grating was also investigated and adequate annealing condition was estimated to obtain sufficient stability for practical use in dense WDM transmission.

In a variety of communication systems, the multipath propagation due to various reflections is often encountered. In this paper, the directions-of-arrival (DOA) estimation of the cyclostationary coherent signals is investigated. A new approach is proposed for estimating the DOA of the coherent signals impinging on a uniform linear array (ULA) by utilizing the spatial smoothing (SS) technique. In order to improve the robustness of the DOA estimation by exploiting the cyclic statistical information sufficiently and handling the coherence effectively, we give a cyclic algorithm with multiple lag parameters and the optimal subarray size. The performance of the presented method is verified and compared with the conventional methods through numerical examples.

An efficient algorithm is proposed to identify the active users and extracting their respective timing information in asynchronous direct sequence CDMA (DS-CDMA) communication system over Rayleigh fading channel. The joint identification and timing estimation algorithm is derived by performing discrete Fourier transform (DFT) on the observation vector and exploiting the uniqueness and nullity characteristics of the root-MUSIC test polynomial. The root-MUSIC based algorithm is shown to be asymptotically near-far resistant. Compared to the maximum a posteriori (MAP) or maximum likelihood (ML) based multiuser timing estimator, the complexity is greatly reduced by separating the multi-dimensional optimization problem into several polynomial rooting problems. Moreover, we characterize the dependence of system performance with respect to signature sequence length, number of active users, window size, desired user's signal-to-noise ratio (SNR) and crosscorrelation property of the code structure. The analytical results reveal that under the uncorrelated Rayleigh fading model, the root-MUSIC timing estimator tends to achieve the Cramer-Rao lower bound (CRLB) at interesting signature sequence length and desired user's SNR.