In this paper, class DE inverter with second order constant K band-pass filter is proposed. In the proposed inverter, the band-pass filter is used instead of the resonant filter in class DE inverter presented at the previous papers. By using band-pass filter, two important results can be gotten. One is the sensitivity of the output voltage to the operating frequency is suppressed by using band-pass filter. The other is that zero voltage switching operation appears when the operating frequency is lower than the nominal frequency. Moreover, it keeps the advantage of class DE inverter with resonant filter, that is, high power conversion efficiency under high frequency operation because of class E switching. The laboratory experiments achieve 90.4% power conversion efficiency under 1.98 W output power and 1.0 MHz operation.

We recorded time series data of calls of Japanese tree frogs (Hyla japonica; Nihon-Ama-Gaeru) and examined the dynamics of the experimentally observed data not only through linear time series analysis such as power spectra but also through nonlinear time series analysis such as reconstruction of orbits with delay coordinates and different kinds of recurrence plots, namely the conventional recurrence plot (RP), the iso-directional recurrence plot (IDRP), and the iso-directional neighbors plot (IDNP). The results show that a single frog called nearly periodically, and a pair of frogs called nearly periodically but alternately in almost anti-phase synchronization with little overlap through mutual interaction. The fundamental frequency of the calls of a single frog during the interactive calling between two frogs was smaller than when the same frog first called alone. We also used the recurrence plots to study nonlinear and nonstationary determinism in the transition of the calling behavior. Moreover, we quantified the determinism of the nonlinear and nonstationary dynamics with indices of the ratio R of the number of points in IDNP to that in RP and the percentage PD of contiguous points forming diagonal lines in RP by the recurrence quantification analysis (RQA). Finally, we discuss a possibility of mathematical modeling of the calling behavior and a possible biological meaning of the call alternation.

In this paper, two new clustering algorithms are proposed for the data with some errors. In any of these algorithms, the error is interpreted as one of decision variables -- called "tolerance" -- of a certain optimization problem like the previously proposed algorithm, but the tolerance is determined based on the opposite criterion to its corresponding previously proposed one. Applying our each algorithm together with its corresponding previously proposed one, a reliability of the clustering result is discussed. Through some numerical experiments, the validity of this paper is discussed.

In this paper, a novel decentralized adaptive neural network controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, nonaffine subsystems and unknown nonlinear interconnections. The stability of the closed loop system is guaranteed by introducing a robust adaptive bound based on Lyapunov stability analysis. A radial-basis function type neural network is used in the paper. To show the effectiveness of the proposed method, we performed some simulation studies. The results of simulation become very promising.

The present paper introduces a new construction of a class of binary periodic sequence set having a zero-correlation zone sequence set. The cross-correlation function and the side-lobe of the auto-correlation function of the proposed sequence set is zero for the phase shifts within the zero-correlation zone. The present paper shows that such a construction generates a binary zcz sequence set by using an arbitrary pair of an even-perfect sequence and an odd-perfect sequence. The proposed zcz sequence set reaches the theoretical upper bound of the member size of the sequence set.

This paper reviews our recent antennas and propagation studies for MIMO systems. First we introduce a MIMO propagation channel model in which an interesting nature can be found in eigenvalue statistics from a practical viewpoint. Then we introduce multi-keyhole model which is an efficient tool for designing a MIMO repeater systems, or MIMO radio-relay systems. For realization of compact MIMO antenna systems, effectiveness of using multiple polarizations such as dual polarizations and triple polarizations is demonstrated in multipath-rich propagation environments. With application of MIMO to OFDM systems, we focus our analysis on relation between propagation and digital transmission characteristics under a severe multipath-rich environment where the delay profile exceeds the guard interval. Finally, we discuss transmission characteristics of MIMO-OFDM with maximal ratio combining (MRC) diversity in the environment.

We prove that the Variational distance (and its positive multiples) is the only f-divergence that satisfies both the identity of indiscernibles and the triangle inequality. Therefore it is the unique f-divergence which serves as a metric. This point is interpreted as a fundamental confliction of the convexity for f(x) with the metric properties for its associated f-divergence. Therefore, we relax the convexity of f(x) and replace it with other constraints to create new metrics.

DTW-based text-dependent speaker verification technology is an effective scheme for protecting personal information in personal electronic products from others. To enhance the performance of a DTW-based system, an impostor database covering all possible passwords is generally required for the matching scores normalization. However, it becomes impossible in our practical application scenario since users are not restricted in their choice of password. We propose a method to generate pseudo-impostor data by employing an acoustic codebook. Based on the pseudo-impostor data, two normalization algorithms are developed. Besides, a template compression approach based on the codebook is introduced. Some modifications to the conventional DTW global constraints are also made for the compressed template. Combining the normalization and template compression methods, we obtain more than 66% and 35% relative reduction in storage and EER, respectively. We expect that other DTW-based tasks may also benefit from our methods.

Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP).The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods.

There have been many theoretical and experimental investigations on polarization diversity reception characteristics at base stations. The diversity gain was evaluated based on the distribution of the instantaneous received power in these investigations. The mainstream mobile communication systems are shifting to standardized IMT-2000 systems and the W-CDMA system is one of them. The effect using base station polarization diversity in W-CDMA must be evaluated by considering not only antenna diversity, but also RAKE reception/path diversity. Furthermore, Transmit Power Control (TPC) is applied to overcome the near-far problem of mobile units that maintain a fixed reception power level in W-CDMA systems. Therefore, traditional diversity gain cannot be used as an evaluation metric. This paper proposes a theoretical analysis method for diversity gain using base station polarization diversity in W-CDMA. The evaluation model used for theoretical analysis is verified based on a comparison with the experimental results and the analytical results of the practical diversity gain are clarified.

In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pair (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods by investigating the distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. Next, the proposed techniques are applied to the predictive vector quantizer (PVQ) used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064 dB and the percentage of outliers compared with the PVQ without any compensation, resulting in transparent quality of spectral quantization. Finally, the comparison of speech quality using the perceptual evaluation of speech quality (PESQ) measure is performed and it is shown that the IS-641 speech coder employing the proposed techniques has better decoded speech quality than the standard IS-641 speech coder.

3D video, which consists of a sequence of mesh models, can reproduce dynamic scenes containing 3D information. To summarize 3D video, a key frame extraction method is developed using rate-distortion (R-D) trade-off. For this purpose, an effective feature vector is extracted for each frame. Shot detection is performed using the feature vectors as a preprocessing followed by key frame extraction. Simple but reasonable definitions of rate and distortion are presented. Based on an assumption of linearity, an R-D curve is generated in each shot, where the locations of the key frames are optimized. Finally, R-D trade-off can be achieved by optimizing a cost function using a Lagrange multiplier, where the number of key frames is optimized in each shot. Therefore, our system will automatically determine the best locations and the number of key frames in the sense of R-D trade-off. Our experimental results show the extracted key frames are compact and faithful to the original 3D video.

We consider the blind recovery problem such that images embedded with side information are given, and we want to obtain the side information under some prescribed constraints. In this case, the system equation becomes y=Ax+b where in addition to the unknown A and x, b also is an unknown quantity and but clearly not a noise component. We assume that several images with the same embedding side information are given, and the image processing to b is described as the perturbation of A. We formulate the optimization function to obtain A, b and x, under the constraint of some finite brightness levels i.e. finite alphabets.

In this letter we introduce new generalized cyclotomic sequences of order two and length pq firstly, then we determine the linear complexity and autocorrelation values of these sequences. Our results show that these sequences are rather good from the linear complexity viewpoint.

Steganographic methods usually produce distortions in cover images due to the process of embedding secret bits. These distortions are hard to remove, and thus the cover image cannot be recovered. Although the distortions are always small, they cannot be allowed for some sensitive applications. In this paper, we propose a reversible embedding scheme for VQ-compressed images, which allows the original cover image to be completely recovered after the extraction of the secret bits. The embedded payload in the proposed method comprises the secret bits plus the restoration information. In order to reduce the size of payload, we utilized the spatial correlations in the image as the restoration information and then compressed the correlations by a lossless compression method. In addition, an alternative pairing method for codewords was proposed to improve the stegoed image quality and control the embedding capacity. Experimental results showed that the proposed method has the benefit of high efficiency of the steganographic process, high image quality, and adaptive embedding capacity compared with other schemes.

A cyclic prefix reconstruction scheme is proposed for precoded single-carrier systems with frequency-domain equalization (SC-FDE) that employ insufficient length of cyclic prefix. For SC-FDE, cyclic prefix is employed to facilitate frequency-domain equalization at the receiver. Since inserting cyclic prefix incurs a loss in bandwidth-utilization efficiency, it is desirable to limit the length of cyclic prefix for SC-FDE. This paper designs the energy spreading transform (EST), a precoder that enables iterative reconstruction of missing cyclic prefix. The performance of the proposed scheme is shown to be close to that of SC-FDE with enough length of cyclic prefix.

Flexibility, adaptation and distribution have been regarded as major challenges of modern interorganizational workflow. To address these issues, this paper proposes an interorganizational workflow execution framework based on process agents and ECA rules. In our framework, an interorganizational workflow is modeled as a multiagent system with a process agent for each organization. The whole execution is divided into two parts: the intra-execution, which means execution within a same organization, and the inter-execution, which represents interaction between organizations. For intra-execution, we use the method of transforming the graph-based local workflow into block-based workflow to design general ECA rules. ECA rules are used to control internal state transitions and process agents are used to control external state transitions of tasks in the local workflows. Inter-execution is realized by process agent interaction protocols. The proposed approach can provide flexible execution of interorganizational workflow with distributed organizational autonomy and adaptation. A case study of offshore software development is illustrated for the proposed approach.

Endothelial cell adhesion and growth were investigated on three types of surfaces with a plasma-polymerized coating (PPC): (1) the pristine surface of a hexamethyldisiloxane (HMDS) PPC (hydrophobic, electrically neutral surface); (2) an HMDS PPC surface with nitrogen-containing plasma treatment (hydrophilic, positively charged surface); and (3) an HMDS PPC surface treated with oxygen plasma (hydrophilic, negatively charged surface). Endothelial cells grew on surface (2) but not on surfaces (1) or (3). Next, endothelial cell adhesion and growth was investigated on a surface on which 80-µm squares were micro-patterned at 160-µm intervals in a mosaic composed of two different (cell-adhesive and non-cell-adhesive) regions. Cell growth on the patterned surfaces was different from that on non-patterned surfaces. PPC was shown to be a simple process for modulating cell adhesion to surfaces.

Skin tone detection in conditions where illuminate intensity and/or chromaticity can vary often comes with high computational time or low accuracy. Here a technique is presented integrating chromaticity and intensity normalization combined with a neural skin tone classification network to achieve robust classification faster than other approaches.

In statistical pattern recognition, it is important to estimate the distribution of patterns precisely to achieve high recognition accuracy. In general, precise estimation of the parameters of the distribution requires a great number of sample patterns, especially when the feature vector obtained from the pattern is high-dimensional. For some pattern recognition problems, such as face recognition or character recognition, very high-dimensional feature vectors are necessary and there are always not enough sample patterns for estimating the parameters. In this paper, we focus on estimating the distribution of high-dimensional feature vectors with small number of sample patterns. First, we define a function, called simplified quadratic discriminant function (SQDF). SQDF can be estimated with small number of sample patterns and approximates the quadratic discriminant function (QDF). SQDF has fewer parameters and requires less computational time than QDF. The effectiveness of SQDF is confirmed by three types of experiments. Next, as an application of SQDF, we propose an algorithm for estimating the parameters of the normal mixture. The proposed algorithm is applied to face recognition and character recognition problems which require high-dimensional feature vectors.