Recently, studies and developments of Collision Warning System (CWS) have attracted widely a particular attention among various wave applications at 60 GHz frequency band. Major performance of the CWS is given by the maximum detection range, the minimum detectable width and accuracy of detection distance. Since the maximum detection range and the minimum detectable width depend on a size of a target, it is important to know Radar Cross Section (RCS) of the target. RCS data should be measured so-called far field condition (greater than a few hundreds meters), while CWS is usually used in the range of 20-100 m. Therefore, a measurement of the reflection characteristics in shorter distance should be necessarily known. In this study, we present reflection characteristics of a medium size truck and a passenger car measured in open field at 60 GHz frequency. It is concludingly described that the reflection characteristics of the passenger car and the medium size truck are 13-18 dBm2 and 15-32 dBm2, respectively, for a case of horizontal polarization.

This paper describes an efficient method to simulate lossy coupled transmission lines based on the delay evaluation technique. First, we review the previous methods, and refer to several problems concerned with these methods. Next, a novel waveform relaxation-based simulation method is proposed, which uses the delay evaluation technique. This method enables to obtain the accurate transient waveforms using smaller number of moments than the other moment methods use, and is modified for acceleration by the generalized line delay window partitioning (GLDW) technique. Finally, this method is implemented in the waveform relaxation-based circuit simulator DESIRE3T+, and the performance is estimated.

In this paper, a modified multi-step SIR-based down-link power control method is proposed. The main idea is to predict the variation of Rayleigh fading from the received signal-to-interference ratio and then to track it in time. A computer program is developed to simulate the performances of this new method as well as the original multi-step SIR-based method. Simulation results show that, of the two, the former performs better than the latter, even if the bit error rate of power control command is around 0. 001.

The TMN that appears to operate the various communication networks generally and efficiently is developed under the different platform environment such as the different hardware and the different operating system. One of the main problems is that all the agents of the TMN system must be duplicated and maintain the software and the data blocks that perform the identical function. Therefore, the standard of the Q3 interface development cannot be defined and the multi-platform cannot be supported in the development of the TMN agent. In order to overcome these problems, the Farming methodology that is based on the Farmer model has been suggested. The main concept of the Farming methodology is that the software and the data components that are duplicated and stored in each distributed object are saved in the Platform Independent Class Repository (PICR) by converting into the format of the independent componentware in the platform, so that the componentwares that are essential for the execution can be loaded and used statically or dynamically from PICR as described in the framework of each distributed object. The distributed TMN agent of the personal communication network is designed and developed by using the Farmer model.

This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ,m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e. g. , SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ,m)s or a parallel construction of the H original GLFSR(δ,m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test time. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.

We present experimental results for a structural learning method of feed-forward neural-network classifiers using Principal Component Analysis (PCA) network and Species Genetic Algorithm (SGA). PCA network is used as a means for reducing the number of input units. SGA, a modified GA, is employed for selecting the proper number of hidden units and optimizing the connection links. Experimental results show that the proposed method is a useful tool for choosing an appropriate architecture for high dimensions.

For people with serious disability, it is most significant to be able to use the same communication methods, for instance a telephone and an electronic mail system (e-mail), as ordinary people do in order to get a normal life and communicate with other people for leading a social life. In particular, having communications access to an e-mail is a very effective method of communication that enables them to convey their intention to other people directly while at the same time keep their privacy. However, it takes them much time and effort to input an e-mail text on the computer. They also need much support by their attendants. From this point of view, we propose a multi-modal communication system that is composed of a voice recognizer, a pointing device, and a text composer. This system intend to improve the man-machine interface for people with physical disability. In this system, our voice recognition technology plays a key role in providing a good interface between disabled people and the personal computer. When generating e-mail contents, users access the database containing user keywords, and the guidance menu from which they select the appropriate word by voice. Our experimental results suggest that this communication system improves not only the time efficiency of text composition but also the readiness of disabled people to communicate with other people. In addition, our disabled subject on this paper is not able to move his body, legs and hands due to suffer from muscular dystrophy. And he is able to move only his fingers and speak command words with the assistance of a respirator.

In this paper, a new traffic sign detection algorithm and a symbol recognition algorithm are proposed. For a traffic sign detection, a dominant color transform is introduced, which serves as a tool of highlighting a dominant primary color, while discarding the other two primary colors. For a symbol recognition, the curvilinear shape distribution on a circle centered on the centroid of the symbol, called a circular pattern vector, is used as a spatial feature of the symbol. The circular pattern vector is invariant to scaling, translation, and rotation. As simulation results, the effectiveness of traffic sign detection and recognition algorithms are confirmed.

This paper proves a general sampling theorem, which is an extension of Shannon's classical theorem. Let o be a closed subspace of square integrable functions and call o a signal space. The main aim of this paper is giving a necessary and sufficient condition for unique existence of the sampling basis {Sn}o without band-limited assumption. Using the general sampling theorem we rigorously discuss a frequency domain treatment and a general signal space spanned by translations of a single function. Many known sampling theorems in signal spaces, which have applications for multiresolution analysis in wavelets theory are corollaries of the general sampling theorem.

The second-generation CMOS current conveyors are developed for high-frequency analog signal processing. It consists of a source follower for the voltage input and a regulated current mirror for the current input and output. The voltage and current input stages are also coupled by a current mirror to reduce the impedance of the current input port. Simulations show that this architecture provides the high input/output conductance ratio and the inherent voltage and current transfer bandwidths extending beyond 100 MHz. The prototype chips fabricated using 0. 6 µm CMOS process have confirmed the simulated performances, though the voltage and current bandwidth are limited to 20 MHz and 35 MHz, respectively, by the built-in capacitances of the bonding pads.

A novel phase compensation technique for feedback integrators is proposed. By the technique, a zero is obtained without employing extra capacitors. A design of an integrator for IC using the proposed technique is presented. The frequency of the parasitic pole is proportional to the unity gain frequency. It is shown that excess-phase cancellation is obtained at any unity gain frequency.

In this letter, a digital circuit realizing a Rossler model is proposed. The proposed circuit features exact reproducibility of chaos signals which is desired in chaos-based communication systems. By employing an FPGA implementation, the proposed circuit can achieve high-speed and low-cost realization. The chaotic behavior of the quasi-chaos of the proposed circuit is analyzed by numerical simulations. To confirm the validity of the FPGA implementation, the proposed circuit is designed by using an FPGA CAD tool, Verilog-HDL. This circuit design showed that the proposed circuit can be implemented onto a single FPGA and can realize real-time chaos generation.

This paper deals with a set of differential operators for calculating the differentials of an observed signal by the Daubechies wavelet and its application for the estimation of the transfer function of a linear system by using non-stationary step-like signals. The differential operators are constructed by iterative projections of the differential of the scaling function for a multiresolution analysis into a dilation subspace. By the proposed differential operators we can extract the arbitrary order differentials of a signal. We propose a set of identifiable filters constructed by the sum of multiple filters with the first order lag characteristics. Using the above differentials and the identifiable filters we propose an identification method for the transfer function of a linear system. In order to ensure the appropriateness and effectiveness of the proposed method some numerical simulations are presented.

We propose a Generalized Order Statistic Cell Averaging (GOSCA) CFAR detector. The weighted sums of the order statistics in the leading and lagging reference windows are utilized for the background level estimate. The estimate is obtained by averaging the weighted sums. By changing the weighting values, various CFAR detectors are obtained. The main advantage of the proposed GOSCA CFAR detector over the GOS CFAR detector is to reduce a computational time which is critical factor for the real time operation. We also derive unified formulas of the GOSCA CFAR detector under the noncoherent integration scheme. For Swerling target cases, performances of various CFAR detectors implemented using the GOSCA CFAR detector are derived and compared in homogeneous environment, and in the case of multiple targets and clutter edges situations.

In this paper, an FPGA (Field Programmable Gate Array)-implementable digital chaos circuit with nonlinear mapping function learning ablility is proposed. The features of this circuit are user-programmability of the mapping functions by on-chip supervised learning, robustness of chaos signal generation based on digital processing, and high-speed and low-cost thanks to its FPGA implementation. The circuit design and analysis are presented in detail. The learning dynamics of the circuit and the quantitization effect to the quasi-chaos generation are analyzed by numerical simulations. The proposed circuit is designed by using an FPGA CAD tool, Verilog-HDL. This confirmed that the one-dimensional chaos circuit block (except for SRAM's) is implementable on a single FPGA chip and can generate quasi-chaos signals in real time.

In [1], approximate eigenvalues and eigenvectors are defined and algorithms to compute them are described. However, the algorithms require a certain condition: the eigenvalues of M modulo S are all distinct, where M is a given matrix with polynomial entries and S is a maximal ideal generated by the indeterminate in M. In this paper, we deal with the construction of approximate eigenvalues and eigenvectors when the condition is not satisfied. In this case, powers of approximate eigenvalues and eigenvectors become, in general, fractions. In other words, approximate eigenvalues and eigenvectors are expressed in the form of Puiseux series. We focus on a matrix with univariate polynomial entries and give complete algorithms to compute the approximate eigenvalues and eigenvectors of the matrix.

This paper presents a technique to transmit 16QAM signals in mobile radio environments by using extended symbol-aided estimation (ESAE) method for compensating the multipath fading effect. The main results of this paper are the symbol error rate (SER) performance analyses for BPSK and 16QAM systems using the proposed estimation method under Rician fading. The analytical results demonstrate better performance of the proposed systems compared with those of the conventional systems under fast and severe fading, especially in the region of high signal to noise ratio.

The following, which is related to the design of the microwave filters, is mainly presented: (1) certain useful approximation which can be obtained by double-resistive- terminated 2-ports consisting of a cascade of two 1-variable 2-ports in different variables, and (2) an approach for filter design from 2-variable viewpoint. Approximations presented provide useful magnitude responses in 2-D domain. Hence it is discussed that how the provided 2-D responses can be used for the design of the microwave filters. Furthermore, properties of the 2-variable transfer functions resulting in such circuits are given.

The conventional method requires a centerline of a vessel to estimate the vessel diameter. Two methods of estimating the centerline of vessels have been reported: One is to manually define the centerline of the vessel. This potentially contributes to inter- and intra-observer variability. The orientation of the centerline has an effect on the diameter function since diameters are computed perpendicular to the centerline. And the other is to automatically detect the centerline of the vessel. But this is a very complicated method. In this paper, we propose a new method of estimating vessel diameter using direction codes without detecting centerline. Since this method detects the vessel boundary and direction code at the same time, it simplifies the procedure and reduces execution time in estimating the vessel diameter. Compared to a method that automatically estimates the vessel diameter using centerline, a proposed method provides an improved accuracy in image with poor contrast, branching or obstructed vessels. Also, this provides a good compression of boundary description. Our experiments demonstrate the usefulness of the technique using direction code for quantitative angiography. Experimental results justify the validity of the proposed method.

The matrix decomposition of transformation associated with the Kronecker product not only provides a thoughtful structure in hardware realization but also bestows a skillful tool for complexity evaluation. Hence, there are several fast algorithms developed to achieve efficient computation of two-dimensional (2-D) discrete cosine transform (DCT) with matrix decomposition techniques. However, we found that their derivations associated with their computation structures were not shown formally. In this paper, we propose formal derivations to remedy their deficiencies to achieve more structural 2-D DCT and inverse DCT (IDCT) algorithms. Furthermore, we also show that the remedied algorithms are with less computational complexity and more regular structure for realization.