We propose an optical switch control procedure for the Active Optical Access System (AOAS). Optical switches are used in AOAS instead of optical splitters in PON. In the proposed procedure, an OLT determines the switching schedules of optical switches on OSW (Optical Switching Unit) which is installed between OLT and ONU, and informs the OSW of them with a switch control frame preceding of data frame transmission. Then the switch controller on OSW controls the optical switches based on the switching schedules. We developed the prototype systems of OSW, OLT, and ONU. We implemented the optical switch control function with logic circuits on the prototype systems. We demonstrate the proposed procedure works effectively with logic circuits. We also evaluate the 10 Gps optical signal transmission between OLT and ONU. We demonstrate the receiver sensibility on OLT and ONU achieves the distance of 40 km for optical signals transmission with FEC (Forward Error Correction). These receivers are applicable for both AOAS and 10G-EPON.

In the present paper, we propose an evolutionary P2P networking technique that dynamically and adaptively optimizes several P2P network topologies, in which all of the nodes are included at the same time, in an evolutionary manner according to given evaluation criteria. In addition, through simulations, we examine whether the proposed evolutionary P2P networking technique can provide reliable search capability in dynamic P2P environments. In simulations, we assume dynamic P2P environments in which each node leaves and joins the network with its own probability and in which search objects vary with time. The simulation results show that topology reconstruction by the evolutionary P2P networking technique is better than random topology reconstruction when only a few types of search objects are present in the network at any moment and these search objects are not replicated. Moreover, for the scenario in which the evolutionary P2P networking technique is more effective, we show through simulations that when each node makes several links with other nodes in a single network topology, the evolutionary P2P networking technique improves the reliable search capability. Finally, the number of links that yields more reliable search capability appears to depend on how often nodes leave and join the network.

In this paper we investigate a low complexity channel estimation and data transmission scheme for bi-directional relaying networks. We also propose a semi-orthogonal pilot structure for channel estimation to increase the efficiency of data transmission between the Base Station (BS) and Mobile Station (MS) via a fixed Relay Node (RN).

Traditional wavelet-based speech enhancement algorithms are ineffective in the presence of highly non-stationary noise because of the difficulties in the accurate estimation of the local noise spectrum. In this paper, a simple method of noise estimation employing the use of a voice activity detector is proposed. We can improve the output of a wavelet-based speech enhancement algorithm in the presence of random noise bursts according to the results of VAD decision. The noisy speech is first preprocessed using bark-scale wavelet packet decomposition ( BSWPD ) to convert a noisy signal into wavelet coefficients (WCs). It is found that the VAD using bark-scale spectral entropy, called as BS-Entropy, parameter is superior to other energy-based approach especially in variable noise-level. The wavelet coefficient threshold (WCT) of each subband is then temporally adjusted according to the result of VAD approach. In a speech-dominated frame, the speech is categorized into either a voiced frame or an unvoiced frame. A voiced frame possesses a strong tone-like spectrum in lower subbands, so that the WCs of lower-band must be reserved. On the contrary, the WCT tends to increase in lower-band if the speech is categorized as unvoiced. In a noise-dominated frame, the background noise can be almost completely removed by increasing the WCT. The objective and subjective experimental results are then used to evaluate the proposed system. The experiments show that this algorithm is valid on various noise conditions, especially for color noise and non-stationary noise conditions.

Recently, the marginalized particle filter (MPF) has been applied to blind symbol detection problems over selective fading channels. The MPF can ease the computational burden of the standard particle filter (PF) while offering better estimates compared with the standard PF. In this paper, we investigate the application of the blind MPF detector to more realistic situations where the systems suffer from analog imperfections which are non-linear signal distortion due to the inaccurate analog circuits in wireless devices. By reformulating the system model using the widely linear representation and employing the auxiliary variable resampling (AVR) technique for estimation of the imperfections, the blind MPF detector is successfully modified to cope with the analog imperfections. The effectiveness of the proposed MPF detector is demonstrated via computer simulations.

Fractals are mathematical or natural objects that are made of parts similar to the whole in certain ways. In this paper a software reliability forecasting method of software failure is proposed based on predictability of fractal time series. The empirical failure data (three data sets of Musa's) are used to demonstrate the performance of the reliability prediction. Compared with other methods, our method is effective.

A novel method to efficiently synthesize hardware from a large behavioral description in behavioral synthesis is proposed. For a program with functions executable in parallel, this proposed method determines a behavioral partitioning which simultaneously minimizes the overall datapath area and the complexity of the controller while maximizing performance of a synthesized circuit by fully exploiting function-level parallelism of a behavioral description. This method is formulated as an integer programming problem. Experimental results demonstrate that this method leads to a shift of the explorable design space so that superior solutions which could not be explored by earlier work are included, showing the effectiveness of our proposed method.

A band-pass bilateral filter is an improved variant of a bilateral filter that does not have low-pass characteristics but has band-pass characteristics. Unfortunately, its computation time is relatively large since all pixels are subjected to Gaussian calculation. To solve this problem, we pay attention to a nonlinear filter called ε-filter and propose an advanced ε-filter labeled band-pass ε-filter. As ε-filter has low-pass characteristics due to spatial filtering, it does not enhance the image contrast. On the other hand, band-pass ε-filter does not have low-pass characteristics but has band-pass characteristics to enhance the image contrast around edges unlike ε-filter. The filter works not only as a noise reduction filter but also as an edge detection filter depending on the filter setting. Due to its simple design, the calculation cost is relatively small compared to the band-pass bilateral filter. To show the effectiveness of the proposed method, we report the results of some comparison experiments on the filter characteristics and computational cost.

A wireless power link utilizing inductive coupling is developed between stacked chips. In this paper, we discuss inductor layout optimization and rectifier circuit design. The inductive-coupling power link is analyzed using simple equivalent circuit models. On the basis of the analytic models, the inductor size is minimized for the given required power on the receiver chip. Two kinds of full-wave rectifiers are discussed and compared. Various low-power circuit design techniques for rectifiers are employed to decrease the substrate leakage current, reduce the possibility of latch-up, and improve the power transmission efficiency and the high-frequency performance of the rectifier block. Test chips are fabricated in a 0.18 µm CMOS process. With a pair of 700700 µm2 on-chip inductors, the test chips achieve 10% peak efficiency and 36 mW power transmission. Compared with the previous work the received power is 13 times larger for the same inductor size .

To improve speech recognition performance, acoustic feature transformation based on discriminant analysis has been widely used. For the same purpose, discriminative training of HMMs has also been used. In this letter we investigate the effectiveness of these two techniques and their combination. We also investigate the robustness of matched and mismatched noise conditions between training and evaluation environments.

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

This paper proposes a new realization technique of image rejection function by noise-coupling architecture, which is used for a complex bandpass ΔΣAD modulator. The complex bandpass ΔΣAD modulator processes just input I and Q signals, not image signals, and the AD conversion can be realized with low power dissipation. It realizes an asymmetric noise-shaped spectra, which is desirable for such low-IF receiver applications. However, the performance of the complex bandpass ΔΣAD modulator suffers from the mismatch between internal analog I and Q paths. I/Q path mismatch causes an image signal, and the quantization noise of the mirror image band aliases into the desired signal band, which degrades the SQNDR (Signal to Quantization Noise and Distortion Ratio) of the modulator. In our proposed modulator architecture, an extra notch for image rejection is realized by noise-coupled topology. We just add some passive capacitors and switches to the modulator; the additional integrator circuit composed of an operational amplifier in the conventional image rejection realization is not necessary. Therefore, the performance of the complex modulator can be effectively raised without additional power dissipation. We have performed simulation with MATLAB to confirm the validity of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of image-rejection effectively, and improve the SQNDR of the complex bandpass ΔΣAD modulator.

We propose the multi-domain adaptive learning that enables us to find a point meeting possibly time-varying specifications simultaneously in multiple domains, e.g. space, time, frequency, etc. The novel concept is based on the idea of feasibility splitting -- dealing with feasibility in each individual domain. We show that the adaptive projected subgradient method (Yamada, 2003) realizes the multi-domain adaptive learning by employing (i) a projected gradient operator with respect to a ‘fixed’ proximity function reflecting the time-invariant specifications and (ii) a subgradient projection with respect to ‘time-varying’ objective functions reflecting the time-varying specifications. The resulting algorithm is suitable for real-time implementation, because it requires no more than metric projections onto closed convex sets each of which accommodates the specification in each domain. A convergence analysis and numerical examples are presented.

In this paper, we propose a novel noncoherent maximum likelihood detection (NMLD) method for differential spatial multiplexing (SM) multiple-input multiple-output (MIMO) systems. Unlike the conventional maximum likelihood detection (MLD) method which needs the knowledge of channel state information (CSI) at the receiver, NMLD method has no need of CSI at either the transmitter or receiver. After repartitioning the observation block of multiple-symbol differential detection (MSDD) and following a decision feedback process, the decision metric of NMLD is derived by reforming that of MSDD. Since the maximum Doppler frequency and noise power are included in the derived decision metric, estimations of both maximum Doppler frequency and noise power are needed at the receiver for NMLD. A fast calculation algorithm (FCA) is applied to reduce the computational complexity of NMLD. The feasibility of the proposed NMLD is demonstrated by computer simulations in both slow and fast fading environments. Simulation results show that the proposed NMLD has good bit error rate (BER) performance, approaching that of the conventional coherent MLD with the extension of reference symbols interval. It is also proved that the BER performance is not sensitive to the estimation errors in maximum Doppler frequency and noise power.

An eyegaze interface is one of the key technologies as an input device in the ubiquitous-computing society. In particular, an eyegaze communication system is very important and useful for severely handicapped users such as quadriplegic patients. Most of the conventional eyegaze tracking algorithms require specific light sources, equipment and devices. In this study, a simple eyegaze detection algorithm is proposed using a single monocular video camera. The proposed algorithm works under the condition of fixed head pose, but slight movement of the face is accepted. In our system, we assume that all users have the same eyeball size based on physiological eyeball models. However, we succeed to calibrate the physiologic movement of the eyeball center depending on the gazing direction by approximating it as a change in the eyeball radius. In the gaze detection stage, the iris is extracted from a captured face frame by using the Hough transform. Then, the eyegaze angle is derived by calculating the Euclidean distance of the iris centers between the extracted frame and a reference frame captured in the calibration process. We apply our system to an eyegaze communication interface, and verified the performance through key typing experiments with a visual keyboard on display.

This paper proposes a novel crest factor reduction (CFR) algorithm applicable to currently deployed W-CDMA base stations. The peak-to-average ratio (PAR) reduction of the multiple carrier mixed signal, namely CFR, has been an issue in order to convey the benefit of using low-cost power amplifiers. The simple final clipping method (SFCM) as a conventional method has been widely utilized due to its simplicity and effectiveness. However, the SFCM degrades the adjacent channel leakage ratio (ACLR) characteristic as well as the signal quality indicated by either the error vector magnitude (EVM) or the peak code domain error (PCDE). Conventionally, in order to alleviate this undesired deterioration, extra channel filtering and signal quality enhancement followed by CFR might be processed in an open-loop style. Alternatively, to perform CFR by maintaining the PAR as low as possible subject to satisfying the prescribed ACLR and EVM/PCDE performance, this paper introduces the prediction filter dependent peak reduction (PFDPR) process collaboratively working with dynamic waterfilling-based code domain compensation (DWCDC). To verify the superiority of the proposed CFR algorithm, tentative simulations are conducted while maintaining the rules of legitimate W-CDMA base station test specifications.

In this research a new prediction algorithm based on a Fuzzy Mix of Filters (FMF) is developed. The use of a fuzzy mix is a good solution because it makes intuitive the difficult design task of combining several types of filters, so that the outputs of the filters that work closer to their optimal behavior have higher influence in the predicted values. Therefore the FMF adapts, according to the motion of the tracked object or target, the filter weights to reduce the estimation error. The paper develops the theory about the FMF and uses it for applications with hard real-time requirements. The improvement of the proposed FMF is shown in simulation and an implementation on a parallel processor (FPGA) is presented. As a practical application of the FMF, experimental results are provided for a visual servoing task.

This paper presents unconditionally stable and conformal FDTD schemes which are based on the alternating-direction implicit finite difference time domain (ADI-FDTD) method for accurate modeling of perfectly electric conducting (PEC) objects. The proposed schemes are formulated within the framework of the matrix-vector notation of the finite integration technique (FIT), which allows a systematic and consistent extension of finite difference solution of Maxwell's equations on dual grids. As possible choices of second-order convergent conformal method, we apply the partially filled cell (PFC) and the uniformly stable conformal (USC) schemes for the ADI-FDTD method. The unconditional stability and the rates of convergence of the proposed conformal ADI-FDTD (CADI-FDTD) schemes are verified by means of numerical examples of waveguide problems.

The security level of an internet protocol television (IPTV) digital right management (DRM) system ultimately relies on protection of secret keys. Well known devices for the key protection include smartcards and battery backup SRAMs (BB-SRAMs); however, these devices could be vulnerable to various physical attacks. In this paper, we propose a secure and cost-effective design of a cryptographic system on chip (SoC) that integrates the BB-SRAM with a cell-based design technique. The proposed SoC provides robust safeguard against the physical attacks, and satisfies high-speed and low-price requirements of IPTV set-top boxes. Our implementation results show that the maximum encryption rate of the SoC is 633 Mb/s. In order to verify the data retention capabilities, we made a prototype chip using 0.18 µm standard cell technology. The experimental results show that the integrated BB-SRAM can reliably retain data with a 1.4 µA leakage current.

The "geometric AIC" and the "geometric MDL" have been proposed as model selection criteria for geometric fitting problems. These correspond to Akaike's "AIC" and Rissanen's "BIC" well known in the statistical estimation framework. Another well known criterion is Schwarz' "BIC", but its counterpart for geometric fitting has not been known. This paper introduces the corresponding criterion, which we call the "geometric BIC", and shows that it is of the same form as the geometric MDL. Our result gives a justification to the geometric MDL from the Bayesian principle.