Self-connection can enlarge the memory capacity of an associative memory based on the neural network. However, the basin size of the embedded memory state shrinks. The problem of basin size is related to undesirable stable states which are spurious. If we can destabilize these spurious states, we expect to improve the basin size. The inverse function delayed (ID) model, which includes the Bonhoeffer-van der Pol (BVP) model, has negative resistance in its dynamics. The negative resistance of the ID model can destabilize the equilibrium states on certain regions of the conventional neural network. Therefore, the associative memory based on the ID model, which has self-connection in order to enlarge the memory capacity, has the possibility to improve the basin size of the network. In this paper, we examine the fundamental characteristics of an associative memory based on the ID model by numerical simulation and show the improvement of performance compared with the conventional neural network.

A distributed network-oriented Intrusion Detection System (IDS) is a mechanism which detects misuse accesses to an intra-network by distributed IDSs on the network with decomposed attack scenarios. However, there are only ad hoc algorithms for determining a deployment of distributed IDSs and a partition of the attack scenarios. In this paper, we formally define this problem as the IDS partition deployment problem and design an efficient algorithm for a simplified version of the problem by graph theoretical techniques.

The author prepared new composition of Cu-Sn based composite materials containing lamellar solid lubricants, and measured their performance with focus on contact resistance and the coefficient of friction using a low-speed tribo-meter. Among three kinds of composite materials, the composite material containing 26wt.% of total solid lubricants was lower in both of contact resistance and the coefficient of friction and showed stable characteristics compared with those containing 25wt.% and 35wt.% respectively. The author analyzed the characteristics of these materials using several techniques including BSE image, element analysis through EPMA, and mapping analysis, and examined why the composite material containing 26wt.% of total solid lubricants showed higher performance.

An ultra-small (0.3-mm0.3-mm0.06-mm) radio frequency identification chip called the µ-chip has been developed for use in a wide range of individual recognition applications. The chip is designed to be thin enough to be applied to paper and paper-like media that are widely used in retailing to create certificates with monetary value, as well as to token-type devices. The µ-chip has been designed and fabricated using 0.18-µm standard CMOS technology. This ultra-small RFID chip also has a low-cost oriented device structure of a double-surface electrode to simplify the process of connecting the antenna and chip. The measured characteristics of the prototype chip are presented, demonstrating the capability of the new chip as an RFID device.

A statistically uniform E-field is created in a reverberation chamber by moving mechanical stirrers to vary boundary conditions. The uniformity of the spatial electric-field distribution in an ideal reverberation chamber can be theoretically estimated by calculating the probability density function of its distribution. However, uniformity in an actual chamber is affected by the dimensions of the chamber and the structure of the stirrers. We experimentally and theoretically evaluated the effect of stirrers on the spatial uniformity of the average, median, and maximum electric-field distributions. When the dimensions of a chamber equipped with effective stirrers are large compared to the wavelength at the operating frequency, that is, when resonant modes above approximately 105 exist below the operating frequency, the spatial uniformity experimentally evaluated agrees well with theoretical values estimated by calculating the probability density function of their distributions.

A technique for improving the input power dynamic range and extinction ratio of wavelength converters based on cross-gain modulation in a semiconductor optical amplifier is presented.

It is interesting to resolve coherent signals impinging upon a linear sensor array with low computational complexity in array signal processing. In this paper, a computationally efficient method of signal subspace fitting (SSF) for direction-of-arrival (DOA) estimation is developed, based on the multi-stage wiener filter (MSWF). To find the new signal subspace, the proposed method only needs to compute the matched filters in the forward recursion of the MSWF, does not involve the estimate of an array covariance matrix or any eigendecomposition, thus implying that the proposed method is computationally efficient. Numerical results show that the proposed method provides the comparable estimation accuracy with the classical weighted subspace fitting (WSF) method for uncorrelated signals at reasonably high SNR and reasonably large samples, and surpasses the latter for coherent signals in the case of low SNR and small samples. When SNR is low and the samples are small, the proposed method is less accurate than the classical WSF method for uncorrelated signals. This drawback is balanced by the computational advantage of the proposed method.

We calculated the shielding characteristic of a three-dimensional array of strip conductors by using the electric field integral equation method and its expansion to an array structure. From reflection coefficients, the effective permittivity of the array is calculated. The effective permittivity becomes negative in the frequency range above resonance, in which the electromagnetic waves travel through the material in an evanescent mode and the transmission coefficient becomes very small.

This paper proposes a "structuring search space" (SSS) method aimed to accelerate recognition of large character sets. We divide the feature space of character categories into smaller clusters and derive the centroid of each cluster as a pivot. Given an input pattern, it is compared with all the pivots and only a limited number of clusters whose pivots have higher similarity (or smaller distance) to the input pattern are searched in, thus accelerating the recognition speed. This is based on the assumption that the search space is a distance space. We also consider two ways of candidate selection and finally combine them the method has been applied to a practical off-line Japanese character recognizer with the result that the coarse classification time is reduced to 56% and the whole recognition time is reduced to 52% while keeping its recognition rate as the original.

A novel application of fuzzy-neuro approach to protection of double circuit transmission line is demonstrated in this paper. Different system faults on a protected transmission line should be detected and classified rapidly and correctly. Using the proposed approach, fault detection, classification and faulted phase selection could be achieved within a quarter of cycle. Results of performance studies show that the proposed fuzzy-neuro-based module can improve the performance of conventional fault selection algorithms.

This paper proposes a method for estimating the complex permittivity of a small quantity of a sample such as a biological membrane. The feature of this method is that a material with an unknown complex permittivity is mixed with a material with a known complex permittivity in a number of volume ratios. The unknown complex permittivity is estimated by measuring the effective permittivity of the mixtures and by using the mixing formula, which is applied to the composite material. The validity of this estimation method is evaluated using a phospholipid, which is the primary constituent of a biological membrane, in the frequency range from 0.8 GHz to 6 GHz. We confirm that the measured effective permittivity of the phospholipid mixtures, which comprise the phospholipid and Ringer's solution in a number of volume ratios, corresponds to that of the Lichtenecker formula. Additionally, by preparing a number of samples with varying volume ratios the estimation error can be decreased. This estimation method is considered to be effective in the measurement of the complex permittivity for a biological membrane.

The conventional complete discrete wavelet transform (DWT) is shift-sensitive, so that the analysis often becomes unstable. In this paper, we define a measure of shift-sensitivity, based on which we propose a new DWT less sensitive than the complete DWT. The measure is derived from the normalized variation of the output waveform for a shifted signal. The measure indicates that a narrow-band high-pass filter is desirable for shift-insensitivity. Then we propose a new DWT which makes use of a complex filter with half bandwidth of a high-pass filter of an ordinary DWT. In two dimensions, the proposed DWT can decompose an image into either four or six directional components which include two separate diagonals, while the complete DWT decomposes the image into three directional components. We show the effectiveness of our method by evaluating the shift-sensitivity of our DWT and other DWTs. By our DWT a smooth continuing edge of an image can be detected, but by the complete DWT a discontinuous edge is produced.

Footsteps, with different shoes of heels, sneakers, leathers or even bare footed, will appear in different grounds of concrete, wood, etc. If a footstep is discriminable, the application to various fields can be considered. In this paper, the feature extraction of a footstep is investigated. We focus on the recognizing a certain kind of footstep waveforms under the restricted condition. We propose a new methodology using the feature parameter such as the peak frequency set by the mel-cepstrum analysis, the walking intervals and the similarity of spectrum envelope. It is shown for personal identification that the performance of the proposed method is effective.

This paper considers the problem of finding two-dimensional (2-D) direction of arrivals (DOAs) for coherent cyclostationary signals using a 2-D array with random position errors. To alleviate the performance degradation due to the coherence between the signals of interest (SOIs) and the random perturbation in 2-D array positions, a matrix reconstruction scheme in conjunction with an iterative algorithm is presented to reconstruct the correlation matrices related to the received array data so that the resulting correlation matrices possess the eigenstructures required for finding 2-D DOAs. Then, using the reconstructed matrices, we create a subspace orthogonal to the subspace spanned by the direction vectors of the SOIs. Therefore, the 2-D DOAs of the SOIs can be estimated based on a subspace-fitting concept and the created subspace. Finally, several simulation examples are presented for illustration and comparison.

The scaled down feature size and the increased frequency of today's deep sub-micron region call for fundamental changes in driver-load models. To be more specific, new driver-load models need to take into consideration the nonlinear behavior of the drivers, the inductance effects of the loads, and the slew rates of the output waveforms. Current driver-load models use the conventional single Ceff (one-ramp) approach and treat the interconnect load as lumped RC networks. Neither the nonlinear property nor the inductance effects were considered. The accuracy of these existing models is therefore questionable. This paper introduces a new multi-ramp driver model that represents the interconnect load as a distributed RLC network. The employed two effective capacitance values capture the nonlinear behavior of the driver. The lossy transmission line approach accounts for the impact of inductance when modeling the driving point interconnect load. The new model shows improvements of 9% in the average delay error and 2.2% in the slew rate error compared to SPICE.

An estimation method of source location of undesired electromagnetic wave from electronic devices by using the MUSIC algorithm is proposed. The MUSIC algorithm can estimate the direction of arrival accurately, however, the estimation error is large in the case of short range multiple coherent sources. In order to overcome this problem, a method to improve the estimation accuracy is presented. Experimental results show that the proposed method can reduce the maximum estimation error from 7 cm of the conventional method to 2 cm.

A procedure for estimating radiated power of radio transmitter is proposed based on a statistical property of field intensity time variation distribution in a reverberation chamber. When random varying multipath waves produced by stirrers in a reverberation chamber are received together with a direct wave, the resulting mixed waves are regarded as a kind of multipath waves. Theoretical and experimental results are reported regarding a procedure for estimating radiated power from the 63.2% value of CDF (Cumulative Distribution Function) of an envelope of multipath waves.

Short gap arc V-I characteristics are essential to discussions on behavior of contact arc at opening and closing. From this point of view, some conventional arc V-I characteristics were reviewed and inconvenient points of them for practical use were pointed out: (1) not a few electrode-material-dependent constants needed in the equation of V-I relation, (2) difficulty in the prediction of real arc extinction phenomena. In order to overcome these inconveniences, the author measured short gap arc V-I characteristics originally, and tried to formulate them into a simple form on the assumption that the arc column V-I characteristics are little dependent on electrode materials but the unstable arc region is strongly dependent on electrode materials. Measured arc column voltage was directly proportional to the square root of gap length and inversely proportional to the cube root of arc current. Arc became unstable when arc current decreased near to the value generally known as the minimum arc current. It was not necessarily the case that the arc extinguished completely at the minimum arc current, but, depending on the circuit conditions, the arc often existed discontinuously below the so-called minimum arc current. Simple empirical V-I characteristics were proposed for practical use, together with the unstable arc region as the information for arc extinction phenomena.

This paper discusses a generalized concept of multiple-symbol differential detection (MDD) and analytically derives weight parameters based on channel prediction for MDD on fast time-varying channels. At first, this paper shows that adaptive maximum-likelihood sequence estimation employing per-survivor processing (PSP-MLSE) with a single channel tap is similar concept to MDD. Next, the weight parameters for MDD are derived according to the channel estimation of PSP-MLSE based on a high order channel prediction. Finally, computer simulation confirms that MDD with the analytically derived parameters mitigates floor of bit error rate (BER) on fast time-varying fading channels without channel state information.

When a dependency parser analyzes long sentences with fewer subjects than predicates, it is difficult for it to recognize which predicate governs which subject. To handle such syntactic ambiguity between subjects and predicates, we define an "a subject clause (s-clause)" as a group of words containing several predicates and their common subject. This paper proposes a two-phase method for S-clause segmentation. The first phase reduces the number of candidates of S-clause boundaries, and the second performs S-clause segmentation using decision trees. In experimental evaluation, the S-clause information turned out to be effective for determining the governor of a subject and that of a predicate in dependency parsing. Further syntactic analysis using S-clauses achieved an improvement in precision of 5 percent.