Investigations into the suitability of artificial neural network for the prediction of rain attenuation based on radio, meteorological and geographical data from ITU-R data bank are presented. First successful steps towards a prediction model of rain attenuation for radio communication based on adaptive learning from the measurement are made. Rain attenuation prediction with the model based on artificial neural network shows good conformity with the measurement. Moreover, a new evolutionary system, EPNet is used to evolve the artificial neural network rain attenuation model obtained both in architecture and weight, and an optimal rain attenuation model with simpler architecture and better prediction accuracy based on EPNet-evolved artificial neural network is obtained. Compared with the ITU-R model, the EPNet-evolved artificial neural network model of rain attenuation proposed in this paper improves the accuracy of rain attenuation prediction and creates a novel way to predict rain attenuation.

This paper presents a fast inversion method for electromagnetic imaging of cylindrical dielectric objects with the optimal regularization parameter used in the Levenberg-Marquardt method. A novel procedure for choosing the optimal regularization parameter is proposed. The method of moments with pulse-basis functions and point matching is applied to discretize the equations for the scattered electric field and the total electric field inside the object. Then the inverse scattering problem is reduced to solving the matrix equation for the unknown expansion coefficients of a contrast function, which is represented as a function of the relative permittivity of the object. The matrix equation may be solved in the least-squares sense with the Levenberg-Marquardt method. Thus the contrast function can be reconstructed by the minimization of a functional, which is expressed as the sum of a standard error term on the scattered electric field and an additional regularization term. While a regularization parameter is usually chosen according to the generalized cross-validation (GCV) method, the optimal one is now determined by minimizing the absolute value of the radius of curvature of the GCV function. This scheme is quite different from the GCV method. Numerical results are presented for a circular cylinder and a stratified circular cylinder consisting of two concentric homogeneous layers. The convergence behaviors of the proposed method and the GCV method are compared with each other. It is confirmed from the numerical results that the proposed method provides successful reconstructions with the property of much faster convergence than the conventional GCV method.

This paper presents a novel design method for reducing the complexity of the design procedure for diversity antennas on the hand-held phone. Recently, antenna selection diversity has been widely used for hand-held phones in order to overcome a problem of fading. A monopole antenna and an inverted-F antenna are the typical combination for this purpose. In the case of the conventional design method, the mutual coupling between two antennas are used for improving the diversity performance. However, strong mutual coupling often makes the diversity antenna design difficult and degrades the radiation performance. The proposed design method suppresses this coupling by tuning the terminating impedance on the unselected antenna and improves the diversity performance by modifying the shape of inverted-F antenna. The validity of the proposed method is investigated under the effect of the user's hand and head by FDTD simulation.

A low-profile bi-directional cavity antenna has been developed for the IMT-2000 indoor base stations. The geometrical relationships required for the design of an antenna with broadband impedance characteristics, which are obtained as a superposition of two resonant modes (M-antenna + metal case), are presented. The approximate equations describing the resonant frequencies associated with the two resonant modes are derived. By using the equations, a cavity antenna with dimensions of 120 mm 120 mm 12 mm and a fractional bandwidth of 18.3% (VSWR <2) that meets the IMT-2000 specification can be designed successfully. The proposed design procedure of the antenna is confirmed by the measurements.

In this paper, a novel three-port antenna structure, named 180 antenna hybrid, is proposed and demonstrated. This structure is composed of a Wilkinson power divider with the isolation resistor replaced by an aperture-coupled patch antenna. The equivalent series impedance of the antenna can be adjusted to the required one by properly choosing the dimensions of the patch and the coupling aperture. When a signal is fed to the balanced port of this antenna hybrid, the power is equally split, with equal phases, to the two unbalanced ports. No power is radiated out from the antenna. In the other hand, a signal received from the antenna will be split with equal power but 180 phase difference to the two unbalanced ports. The balanced port is an isolation port. The measurement results showed good agreement with the characteristics to be designed. Three applications of this 180 antenna hybrid are introduced, that is, a balanced mixer, an active transmitting antenna, and a dual-radiation-mode antenna array. The balanced mixer was constructed with diodes directly mounted on the two unbalanced ports of the antenna hybrid. The LO signal is fed from the balanced port and RF signal is received from the antenna. The active transmitting antenna was implemented with feedback configuration. The route from one of the unbalanced port to the balanced port of the antenna hybrid was used as the feedback path. A locking signal may be injected from the other unbalanced port. Finally, through a three-quarter-wavelength microstrip line, the balanced port of the antenna hybrid was connected to another aperture-coupled patch antenna to form a dual-radiation-mode antenna array. The in-phase and out-of-phase radiation patterns of this two-element array can be obtained from two unbalanced ports of the antenna hybrid, respectively.

The efficiency-fractional bandwidth product (EB), which is expressed as a ratio of the radiation resistance to the absolute value of the input reactance of an antenna, is used as a performance criterion for small dielectric loaded monopole antennas (DLMAs). The dependence of the EB on the permittivity of the dielectric loading (i.e., the electrical volume) is experimentally and numerically investigated for the first time in antenna research. As a result, it is found that the EBs of the some DLMAs are enhanced over a bare monopole antenna and an EB characteristic curve has a maximum point. This result suggests the presence of the optimum electrical volume for the dielectric loading in order to obtain the best EB performance. A general reason for the existence of the peak value is also explained using a mathematical deduction. Finally the system EB, which is an efficiency-fractional bandwidth product of the DLMA with a practical matching circuit, is defined and its dependence on the relative permittivity is illustrated. Consequently, the existence of the peak value is also confirmed for the system EBs. In addition, it is demonstrated that the enhancement of the system EB is mainly due to the enhancement in the efficiency of the antenna system.

This paper proposes a novel bi-directional rod antenna comprising a narrow patch and parasitic elements for base station antennas of street microcell systems. It is shown that the parasitic elements improve the antenna efficiency of an ordinary bi-directional printed antenna and make it possible to form the antennas using conventional substrates. This paper also proposes a suitable configuration for the array and investigates radiation characteristics of the configuration. Finally, a prototype of the bi-directional rod antenna is presented and the effectiveness of the bi-directional antenna is evaluated.

A polarization diversity planar inverted-F antenna (PIFA) on portable telephone in the practical use near the operator's body is investigated at 1,800 MHz under multipath urban environment. The antenna structure comprises a center-fed square patch with one permanent short-pin and two RF-switches on three corners. The RF-switches perform as the polarization branch switches for dominantly vertical polarization (VP) or dominantly horizontal polarization (HP) modes. The radiation efficiency of the polarization diversity PIFA is 58% and 53% for VP and HP modes, respectively, which is higher than the 52% efficiency of the reference λ/4 monopole antenna under the same condition. The mean effective gain (MEG) of VP and HP modes decrease with respect to the increasing cross-polarization power ratio (XPR). The correlation coefficient of two diversity branches is between 0.66 through all the possible XPR ranging from -10 dB to +10 dB. The diversity gain is computed from the MEG and correlation coefficient to determine the diversity antenna gain (DAG). The diversity gain, based on 10-3 BER for selective combining, is 7.5 dB over non-diversity reception. The DAG is -1.2+2.8 dBi which is approximately 4 dB lower than the case without human body. In other words, the presence of the human body degrades the communication performance by a half.

Currently the long memory behavior is associated to stochastic processes. It can be modeled by different models such like the FARIMA processes, the k-factors GARMA processes or the fractal Brownian motion. On the other side, chaotic systems characterized by sensitivity to initial conditions and existence of an attractor are generally assumed to be close in their behavior to random white noise. Here we show why we can adjust a long memory process to well known chaotic systems defined in dimension one or in higher dimension. Using this new approach permits to characterize in another way the invariant measures associated to chaotic systems and to propose a way to make long term predictions: two properties which find applications in a lot of applied fields.

Particulate media composed of very small particles were studied to determine high-density recording performance and thermal stability. Studied media included metal particulate media with mean particle length of 71, 102 and 148 nm, and Ba ferrite particulate media with mean diameter of 22, 28 and 50 nm. Using a loss-term simulation program, taking into account gap-loss, spacing-loss and particle length loss, the recording capability (D20 of 265 kFRPI for MP and 290 kFRPI for Ba ferrite media) was estimated. Thermal stability was evaluated from magnetization time decay measurements. It was found that MP media with large Ku values and 71 nm particles were satisfactorily stable, and the particle volume is still large enough in respect of thermal stability. However, 22-nm Ba ferrite media were less stable, primarily because of small Ku values and particle volume. It was also clarified that positive inter-particle interaction accelerates magnetization time decay, in the presence of a large reverse field.

There are so many methods of calculating the cylindrical function Zν(x), but it seems that there is no method of calculating Zν(x) in the region of νx and |ν|»1 with high accuracy. The asymptotic series presented by Watson, et al. are frequently used for the numerical calculation of cylindrical function Zν(x) where νx and |ν|»1. However, the function Bm(εx) included in the m'th term of the asymptotic series is known only for m5. Hence, the asymptotic series can not give sufficiently accurate values of the cylindrical functions. The authors attempt to develop programs for the numerical calculation of the cylindrical functions using this asymptotic series. For this purpose, we must know the function Bm(εx) of arbitrary m. We developed a method of calculating Bm(εx) for arbitrary m, and then succeeded in calculating the cylindrical functions in the region νx with high precision.

This paper describes a cumulative distribution function (CDF) of edge direction for detecting road lanes. Based on the assumptions that there are no abrupt changes in the direction and location of road lanes and that the intensity of lane boundaries differs from that of the background, the CDF is formulated, which accumulates the edge magnitude for edge directions. The CDF has distinctive peak points at the vicinity of lane directions due to the directional and the positional continuities of a lane. To obtain lane-related information, we construct a scatter diagram by collecting edge pixels, of which the direction corresponds to the peak point of the CDF, then perform the principal axis-based line fitting for the scatter diagram. Because noises can cause many similar features appear or disappear in an image, to prevent false alarms or miss detection, a recursive estimator of the CDF was introduced, and also a scene understanding index (SUI) was formulated by the statistical parameters of the CDF. The proposed algorithm has been implemented in real time on video data obtained from a test vehicle driven on a typical highway.

Current-voltage characteristics of Cr-doped hydrogenated amorphous silicon-V (Cr/p+a-Si:H/V) analogue memory switching devices have been measured over a wide range of device resistance from several kilo-ohms to several hundred kilo-ohms, and over a temperature range from 13 K to 300 K. Both the bias and temperature dependence of the conductance show similar characteristics to that of metal-insulator heterogeneous materials (i.e. discontinuous or granular metallic films), which are analysed in terms of activated tunnelling mechanism. A modified filamentary structure for the Cr/p+a-Si:H/V switching devices is proposed. The influence of embedded metallic particles on memory switching is analysed and discussed.

This paper deals with the approximation of multi-dimensional chaotic dynamics by using the multi-stage fuzzy inference system. The number of rules included in multi-stage fuzzy inference systems is remarkably smaller compared to conventional fuzzy inference systems where the number of rules are proportional to an exponential of the number of input variables. We also propose a method to optimize the shape of membership function and the appropriate selection of input variables based upon the genetic algorithm (GA). The method is applied to the approximation of typical multi-dimensional chaotic dynamics. By dividing the inference system into multiple stages, the total number of rules is sufficiently depressed compared to the single stage system. In each stage of inference only a portion of input variables are used as the input, and output of the stage is treated as an input to the next stage. To give better performance, the shape of the membership function of the inference rules is optimized by using the GA. Each individual corresponds to an inference system, and its fitness is defined by using the prediction error. Experimental results lead us to a relevant selection of the number of input variables and the number of stages by considering the computational cost and the requirement. Besides the GA in the optimization of membership function, we use the GA to determine the input variables and the number of input. The selection of input variable to each stage, and the number of stages are also discussed. The simulation study for multi-dimensional chaotic dynamics shows that the inference system gives better prediction compared to the prediction by the neural network.

In this paper, we consider the problem of active learning, and give a necessary and sufficient condition of sample points for the optimal generalization capability. By utilizing the properties of pseudo orthogonal bases, we clarify the mechanism of achieving the optimal generalization capability. We also show that the condition does not only provide the optimal generalization capability but also reduces the computational complexity and memory required to calculate learning result functions. Based on the optimality condition, we give design methods of optimal sample points for trigonometric polynomial models. Finally, the effectiveness of the proposed active learning method is demonstrated through computer simulations.

This paper describes the implementation of a proposed image filter into a Discrete-Time Cellular Neural Network (DT-CNN). The three stages that compose the filter are described, showing that the resultant filter is capable of (1) erasing or detecting several concentric shapes simultaneously, (2) thresholding and (3) thinning of gray-scale images. Because the DT-CNN has to fill certain conditions for this filter to be implemented, it becomes a modified version of a DT-CNN. Those conditions are described and also experimental results are clearly shown.

A novel millimeter-wave slotted waveguide array antenna is developed for automotive radar systems. An antenna structure suitable for mass-production is proposed in this paper. The waveguide is composed of two parts; an upper plate and a bottom plate. It is not necessary to contact each other closely because they are divided at the center of the broad wall of the waveguide where the electric current is small. In addition, grating lobes are suppressed by using a cylindrical cavity around each slot and by controlling the slot arrangement without using dielectric material in the waveguide. We have fabricated the proposed antenna by metal injection molding. The measured antenna efficiency results in 55%, which is quite high in comparison with any other conventional low cost millimeter-wave antenna. This efficiency is almost the same as that of the antenna fabricated by precision metal machining. In this paper, it is confirmed that the proposed antenna could be manufactured with low cost.

We have experimentally observed chaotic oscillation of outputs in a diode-pumped Nd:YAG microchip laser array with an external Talbot mirror. The oscillation of chaotic output is observed at frequencies of sub MHz corresponding to the relaxation oscillation frequencies when the Talbot mirror is slightly tilted from the perfect alignment position with the internal cavity. Chaotic intermittent bursts also appear at frequencies of sub kHz due to longitudinal mode hopping. Synchronization of chaos is observed at these two different time scales. The generation of chaotic oscillations at sub MHz is confirmed by using numerical simulations. It is found that synchronized chaotic oscillations can be observed in the vicinity of the boundary of the injection locking range.

Feature subset selection basically depends on the design of a criterion function to measure the effectiveness of a particular feature or a feature subset and the selection of a search strategy to find out the best feature subset. Lots of techniques have been developed so far which are mainly categorized into classifier independent filter approaches and classifier dependant wrapper approaches. Wrapper approaches produce good results but are computationally unattractive specially when nonlinear neural classifiers with complex learning algorithms are used. The present work proposes a hybrid two step approach for finding out the best feature subset from a large feature set in which a fuzzy set theoretic measure for assessing the goodness of a feature is used in conjunction with a multilayer perceptron (MLP) or fractal neural network (FNN) classifier to take advantage of both the approaches. Though the process does not guarantee absolute optimality, the selected feature subset produces near optimal results for practical purposes. The process is less time consuming and computationally light compared to any neural network classifier based sequential feature subset selection technique. The proposed algorithm has been simulated with two different data sets to justify its effectiveness.

Most of the image restoration filters proposed so far include parameters that control the restoration properties. For bringing out the optimal restoration performance, these parameters should be determined so as to minimize a certain error measure such as the mean squared error (MSE) between the restored image and original image. However, this is not generally possible since the unknown original image itself is required for evaluating MSE. In this paper, we derive an estimator of MSE called the subspace information criterion (SIC), and propose determining the parameter values so that SIC is minimized. For any linear filter, SIC gives an unbiased estimate of the expected MSE over the noise. Therefore, the proposed method is valid for any linear filter. Computer simulations with the moving-average filter demonstrate that SIC gives a very accurate estimate of MSE in various situations, and the proposed procedure actually gives the optimal parameter values that minimize MSE.