Coherence resonance in propagating spikes generated by noise in spatially distributed excitable media is studied with computer simulation and circuit experiment on the FitzHugh-Nagumo model. White noise is added to the one end of the media to generate spikes, which propagate to the other end. The mean and standard deviation of the interspike intervals of the spikes after propagation take minimum values at the intermediate strength of the added noise. This shows stronger coherence than obtained in the previous studies.

We demonstrate, through numerical simulations, the possibility of trans-oceanic single channel transmission at 160 Gbit/s with no active control. This was achieved using short period dispersion management, which supports short pulse propagation at practical map strengths. We demonstrate that through careful selection and optimisation of the system parameters the performance of this system can be extended. We also define the tolerable limits of the system to the residual dispersion slope and polarisation mode dispersion.

Signal path loss and propagation delay spread were measured at microwave frequencies of 3.35, 8.45, and 15.75 GHz along a straight quasi line-of-sight (LOS) street in an urban environment under different traffic conditions: daytime and nighttime. Comparison between daytime and nighttime measurements reveals that the break points shift toward the base station because of the increase in the effective heights of the road and sidewalk; break points were not seen during the daytime at a mobile antenna height (hm) of 1.6 m. According to the cumulative probabilities of the delay spreads during the nighttime, frequency dependence is not clearly observed and the delay spreads for hm = 1.6 m were clearly larger than those for hm = 2.7 m. This is because a lower hm results in stronger blocking of the LOS wave, as was also observed during the daytime. The plot of path losses versus delay spreads is confirmed to be represented by an exponential curve. The exponential coefficients during the daytime were observed to be greater than those during the nighttime. This indicates that a LOS wave is more likely to be blocked during the daytime.

We demonstrate, through numerical simulations, the possibility of trans-oceanic single channel transmission at 160 Gbit/s with no active control. This was achieved using short period dispersion management, which supports short pulse propagation at practical map strengths. We demonstrate that through careful selection and optimisation of the system parameters the performance of this system can be extended. We also define the tolerable limits of the system to the residual dispersion slope and polarisation mode dispersion.

Many experimentally and theoretically based models have been proposed to predict, quantitatively evaluate, and combat the fading phenomenon in mobile communication systems. However, to the best of the authors' knowledge, up to now there is no objective method to determine which is the most suitable distribution to model the fading phenomenon based on experimental data. In this work, the Minimum Description Length (MDL) criterion for model selection is proposed for that purpose. Furthermore, the MDL analysis is performed for some of the most widely used fading models based on measurements taken in a sub-urban environment.

Multilayer feedforward neural network (MFNN) trained by the backpropagation (BP) algorithm is one of the most significant models in artificial neural networks. MFNNs have been used in many areas of signal and image processing due to high applicability. Although they have been implemented as analog, mixed analog-digital and fully digital VLSI circuits, it is still difficult to realize their hardware implementation with the BP learning function efficiently. This paper describes a special BP algorithm for the logic oriented neural network (LOGO-NN) which we have proposed as a sort of MFNN with quantized weights and multilevel threshold neurons. Both weights and neuron outputs are quantized to integer values in LOGO-NNs. Furthermore, the proposed BP algorithm can reduce high precise calculations. Therefore, it is expected that LOGO-NNs with BP learning can be more effectively implemented as digital type circuits than the common MFNNs with the classical BP. Finally, it is shown by simulations that the proposed BP algorithm for LOGO-NNs has good performance in terms of the convergence rate, convergence speed and generalization capability.

In the culture of marine chlorellas, it is necessary to count the number in order to understand the condition of increase. For that propose, counting by the naked eye using the microscope has been used. However, this method requires a lot of time and work. We have developed the automatic chlorella counter using image processing and neural network. Its effectiveness is confirmed through the experiment.

We study the electromagnetic wave propagation in three-dimensional (3-D) dense random discrete media containing dielectric spheroidal scatterers. We employ a Monte Carlo method in conjunction with the Method of Moments to solve the volume integral equation for the electric field. We calculate the effective permittivity of the random medium through a coherent-field approach and compare our results with a classical mixing formula. A parametric study on the dependence of the effective permittivity on particle elongation and fractional volume is included.

Frequency-selective fading due to multipath propagation is serious hindrance in high-speed TDMA mobile communications. An adaptive antenna has been proposed to reduce the frequency-selective fading and realize path-diversity. This paper presents a criterion which selects multipath signals and weighting factors for combining them. First, we describe a selection criterion which chooses the multipath signals for the path-diversity. We propose a ratio of signal power to error power for the criterion. Furthermore, we propose weighting factors which realize approximately the maximal ratio combining. Computer simulation results show that the proposed selection criterion and weighting factors reveal excellent performance.

To enhance fault tolerance ability of the feedforward neural networks (NNs for short) implemented in hardware, we discuss the learning algorithm that converges without adding extra neurons and a large amount of extra learning time and cycles. Our algorithm modified from the standard backpropagation algorithm (SBPA for short) limits synaptic weights of neurons in range during learning phase. The upper and lower bounds of the weights are calculated according to the average and standard deviation of them. Then our algorithm reupdates any weight beyond the calculated range to the upper or lower bound. Since the above enables us to decrease the standard deviation of the weights, it is useful in enhancing fault tolerance. We apply NNs trained with other algorithms and our one to a character recognition problem. It is shown that our one is superior to other ones in reliability, extra learning time and/or extra learning cycles. Besides we clarify that our algorithm never degrades the generalization ability of NNs although it coerces the weights within the calculated range.

Optical logic gates for OR, AND, NOT, and NOR operations in waveguides consisting of nonlinear material are numerically investigated by means of FD-BPM (Finite Difference Beam Propagation Method). The proposed devices are designed utilizing the self-routing characteristics of nonlinear X-crossing structures when they are operated with one input beam or two. The numerical simulations show that the proposed structures can favorably be applied to optical data processing and computing as fundamental logic gates.

Learning process is essential for good performance when a neural network is applied to a practical application. The backpropagation algorithm is a well-known learning method widely used in most neural networks. However, since the backpropagation algorithm is time-consuming, much research have been done to speed up the process. The block backpropagation algorithm, which seems to be more efficient than the backpropagation, is recently proposed by Coetzee in [2]. In this paper, we propose an efficient parallel algorithm for the block backpropagation method and its performance model in mesh-connected parallel computer systems. The proposed algorithm adopts master-slave model for weight broadcasting and data parallelism for computation of weights. In order to validate our performance model, a neural network is implemented for printed character recognition application in the TiME which is a prototype parallel machine consisting of 32 transputers connected in mesh topology. It is shown that speedup by our performance model is very close to that by experiments.

The propagation characteristic of 670 nm laser light on the array of 10 µm diameter polystyrene micro-sphere was studied. For the linearly arranged array of micro-spheres from one to 12, the propagated light intensity was decreased from 700 mV to 45 mV. However, the propagated light intensity in the air was significantly decreased and it became 2 mV at 60 µm from the optical fiber light source. For the micro-sphere array on the curvilinear line, the light intensity at 12th micro-sphere became 35 mV. This fact means the light was propagated almost same as that on the linear line. Whereas it is expected that three dimensionally crossing optical wave-guide is possible to be fabricated by arranging the micro-spheres.

The conventional back-propagation algorithm cannot be applied to networks of units having hard-limiting output functions, because these functions cannot be differentiated. In this paper, a gradient descent algorithm suitable for training multilayer feedforward networks of units having hard-limiting output functions, is presented. In order to get a differentiable output function for a hard-limiting unit, we utilized that if the bias of a unit in such a network is a random variable with smooth distribution function, the probability of the unit's output being in a particular state is a continuously differentiable function of the unit's inputs. Three simulation results are given, which show that the performance of this algorithm is similar to that of the conventional back-propagation.

Presented in this paper is a neural back propagation algorithm for reconstructing two-dimensional CT images from a small number of projection data. The paper extends the work in [1], in which a backpropagation algorithm is applied to the CT image reconstruction problem. The delta rule of the ordinary backpropagation algorithm is modified using a 'secondary' teaching signal and the 'Resilient backpropagation' scheme. Results obtained are presented along with those of two well known conventional methods: MART and EMML method. A quantitative evaluation reveals the effectiveness of the proposed algorithm.

A new algorithm is proposed for improving the convergence of backpropagtion networks. This algorithm is obtained by combining the conjugate gradient method and the Kalman filter algorithm. Simulation results show that the proposed algorithm can perform satisfactorily in all cases considered.

Printed transmission lines have been extensively examined so far, but results obtained there are all concerned with the waveguiding conductors with no loss and zero thickness, except very few results. We have recently studied the transmission characteristics of printed transmission lines in detail, when the waveguiding conductors have finite conductivity and thickness, and we have found an unexpected effect that we call a "mode extinction effect. " This effect results in significant changes in the dispersion behavior of the printed-transmission-line fundamental mode. For a critical thickness, it may turn out that such transmission line can not use in open structural configuration, but must always be used by putting into a packaging box. In this paper, we discuss thoroughly this important effect and related results from the standpoints of both the dispersion behavior and the vector field plots. We also show the measured results of the attenuation constant.

A three-dimensional beam propagation method based on a finite element scheme is described for the analysis of second harmonic generation devices. For the wide-angle beam propagation analysis, the Pade approximation is applied to the differential operator along the propagation direction. In order to avoid spurious reflection from the computational windows edges, the transparent boundary condition is introduced. Numerical results are shown for quasi-phase matched second harmonic generation devices using periodically domain-inverted LiNbO3 and LiTaO3 waveguides. The influences of the shape of domain-inverted regions and the inversion width on the conversion efficiencies are investigated in detail.

We first reported the simultaneous-propagation effect that the leaky dominant mode can be present on conductor-backed coplanar strips at the same time as the conventional bound dominant mode. We have investigated here numerically and experimentally this effect in detail. Consequently, we have found that it occurs under a certain condition of structural parameters, and also have verified that it affects circuit performance significantly.

The long spikes have been often recorded at the multiples of the electron cyclotron frequency in the ionograms of the topside sounders observed in low latitudes. There has not been sufficient explanation for the physical cause for occourrence of the long spike so far. Here, by interpreting this phenomenon as receiving the trapped cyclotron harmonic wave, some analyses for the length of spike are done not only from the viewpoint of the sweeping property of the frequency spectrum of the transmitted pulse but also from that of the mutual positional relation between the propagation path and the orbit of the sounder. The cause of forming a single spike and a graphical calculation method for the long spike are proposed, respectively. Thus, the cause and the fine structure of long spike consisting of superposed spikes are clarified.