This brief paper describes a background calibration algorithm for a pipelined ADC with an open-loop amplifier using a Split ADC structure. The open-loop amplifier is employed as a residue amplifier in the first stage of the pipelined ADC to realize low power and high speed. However the residue amplifier as well as the DAC suffer from gain error and non-linearity, and hence they need calibration; conventional background calibration methods take a long time to converge. We investigated the split ADC structure for its background calibration with fast convergence, and validated its effectiveness by MATLAB simulation.

Over 100 Gbit/s/ch high-speed optical transmission is required to achieve the high capacity networks that can meet future demands. The coherent receiver, which is expected to yield high frequency utilization, is a promising means of achieving such high-speed transmission. However, it requires a high-speed Analog to Digital Converter (ADC) because the received signal bandwidth would be over several tens or hundreds of GHz. To solve this problem, we propose a band-divided receiver structure for wideband optical signals. In the receiver, received wideband signals are divided into a number of narrow band signals without any guard band. We develop a band-divided receiver prototype and evaluate it in an experiment. In addition, we develop a real-time OFDM demodulator on an FPGA board that implements 1.5 GS/s ADCs. We demonstrate that the band-divided receiver prototype with its real-time OFDM demodulator and 1.5 GS/s ADC can demodulate single polarization 12 Gbit/s OFDM signals in real-time.

In this paper, a robust fractional order memory polynomial pre-distorter with two novel schemes to conduct digital base-band power amplifier pre-distortion is proposed. For the first scheme, fractional order terms are included in the conventional memory polynomial containing the odd and even order polynomial terms, which is called Scheme One. The second scheme, called Scheme Two, simply replaces even order polynomial terms with fractional order polynomial terms to improve the linear performance of power amplifiers. The mathematical expressions for these two schemes are derived. The computer simulations and numerical analysis show that, compared with the conventional pre-distortion methods, 11 dB and 8.5 dB more out-of-band suppression gain can be obtained by Scheme One and Scheme Two, respectively. Corresponding FPGA realization shows that the two schemes are cost-effective in terms of hardware resources.

A 10-Gbit/s-class ac-coupled average-detection-type burst-mode receiver (B-Rx) with an ultra fast response and a high tolerance to the long consecutive identical digits has been developed. Key features of the circuit design are the baseline-wander common-mode rejection technique and the inverted distortion technique adopted in the limiting amplifier to cope with both the fast response and the high tolerance. Our B-Rx with newly developed limiting amplifier IC achieved a settling time of less than 150 ns, a sensitivity of -29.8 dBm, and a dynamic range of 23.8 dB with a 231-1 pseudo random bit sequences. Moreover, we also describe several potential B-Rx applications. We achieved better performance by applying the proposed systems to our B-Rx.

Networks have gotten bigger recently, and users have a more difficult time finding the information that they want. The use of mobile agents to help users effectively retrieve information has garnered a lot of attention. In this paper, we propose an agent control method for time constrained information retrieval. We pay attention to the highest past score gained by the agents and control the agents with the expectation of achieving better scores. Using computer simulations, we confirmed that our control method gave the best improvement over the whole network while reducing the overall variance. From these results, we can say that our control method improves the quality of information retrieved by the agent.

We propose a polarization-multiplexing QPSK modulator for synthesis of a 16 QAM signal. The generation mechanism of 16 QAM is based on an electro-optic vector digital-to-analog converter, which can generate optical multilevel signals from binary electric data sequences. A quad-parallel Mach-Zehnder modulator (QPMZM) used in our previous research requires precise control of electric signals or fabrication of a variable optical attenuator, which significantly raises the degree of difficulty to control electric signals or device fabrication. To overcome this difficulty, we developed the polarization-multiplexing QPSK modulator, which improved the method of superposition of QPSK signals. In the polarization-multiplexing QPSK modulator, two QPSK signals are output with orthogonal polarization and superposed through a polarizer. The amplitude ratio between the two QPSK signals can be precisely controlled by rotating the polarizer to arrange the 16 symbols equally. Generation of 16 QAM with 40 Gb/s and a bit error rate of 5.6910-5 was successfully demonstrated using the polarization-multiplexing QPSK modulator. This modulator has simpler configuration than the previous one, utilized a dual-polarization MZM, alleviating complicated control of electric signals.

This paper firstly analysis the coherent correlation, non-coherent accumulation detector used in weak satellite signal detection mathematically and statistically, and derives its single threshold based on the CFAR (constant false alarm rate). And then the paper improved the detector under the situation of more than one satellite existing with different signal power. Based on this new type of detector, a threshold calculation method is introduced considering the effect of near-far problem in the weak signal detection. Finally the method is verified and compared to the traditional single threshold with simulated data and collected intermediate frequency real data. The results show that this new threshold method can detect signal efficiently with lower false alarm possibility and larger detection possibility.

An optimal selection criterion of the modulation and coding scheme (MCS) for maximizing spectral efficiency is proposed in consideration of the signaling overhead of mobile WiMAX systems with a hybrid automatic repeat request mechanism. A base station informs users about the resource assignments in each frame, and the allocation process generates a substantial signaling overhead, which influences the system throughput. However, the signaling overhead was ignored in previous MCS selection criteria. In this letter, the spectral efficiency is estimated on the basis of the signaling overhead and the number of transmissions. The performance of the proposed MCS selection criterion is evaluated in terms of the spectral efficiency in the mobile WiMAX system, with and without persistent allocation.

Quadratic congruence code (QCC)-based frequency-hopping and time-spreading (FH/TS) optical orthogonal codes (OOCs), and the corresponding expanded cardinality were recently studied to improve data throughput and code capacity. In this paper, we propose a new FH/TS two-dimensional (2-D) code using the QCC and the cubic congruence code (CCC), named as the QCC/CCC 2-D code. Additionally the expanded CCC-based 2D codes are also considered. In contrast to the conventional QCC-based 1-D and QCC-based FH/TS 2-D optical codes, our analysis indicates that the code capacity of the CCC-based 1-D and CCC-based FH/TS 2-D codes can be improved with the same code weight and length, respectively.

In this letter we present efficient iterative frequency domain equalization for single-carrier (SC) transmission systems with insufficient cyclic prefix (CP). Based on minimum mean square error (MMSE) criteria, iterative decision feedback frequency domain equalization (IDF-FDE) combined with cyclic prefix reconstruction (CPR) is derived to mitigate inter-symbol interference (ISI) and inter-carrier interference (ICI). Computer simulation results reveal that the proposed scheme significantly improves the performance of SC systems with insufficient CP compared with previous schemes.

We propose a mechanism called “optical plug and play” for constructing GMPLS networks automatically. It offers lower operation effort and fast network construction, and avoids misconfiguration. Optical plug and play architecture has its procedure, a link-up search mechanism for OXCs, network and node architectures to realize optical plug and play, and an LMP extension to exchange the information between nodes necessary for identifying adjacent nodes. We implement prototypes of both OXCs and routers that support the optical plug and play proposal. Simulations and experiments confirm its performance and feasibility.

The detection of object categories with large variations in appearance is a fundamental problem in computer vision. The appearance of object categories can change due to intra-class variations, background clutter, and changes in viewpoint and illumination. For object categories with large appearance changes, some kind of sub-categorization based approach is necessary. This paper proposes a sub-category optimization approach that automatically divides an object category into an appropriate number of sub-categories based on appearance variations. Instead of using predefined intra-category sub-categorization based on domain knowledge or validation datasets, we divide the sample space by unsupervised clustering using discriminative image features. We then use a cluster performance analysis (CPA) algorithm to verify the performance of the unsupervised approach. The CPA algorithm uses two performance metrics to determine the optimal number of sub-categories per object category. Furthermore, we employ the optimal sub-category representation as the basis and a supervised multi-category detection system with χ2 merging kernel function to efficiently detect and localize object categories within an image. Extensive experimental results are shown using a standard and the authors' own databases. The comparison results reveal that our approach outperforms the state-of-the-art methods.

A planar circularly-polarized (CP) small antenna is proposed. To obtain a low profile configuration, a co-planar waveguide (CPW) structure is employed. Circular polarization is achieved using a curved stub that generates current distribution in a direction orthogonal to the current distribution from the patch. Using meander lines and a series gap capacitance, a 70% size reduction is achieved compared to a half-wavelength resonant antenna. To the best of the authors' knowledge, the proposed antenna is the smallest CP antenna using CPW technology. The measured 3 dB axial ratio bandwidth is 8.3% from 3.83 GHz to 4.16 GHz, and a 1.6 dBic gain and 89% efficiency are achieved.

We demonstrate high baud-rate DQPSK modulation with full-ETDM technique using a novel high-speed optical IQ modulator consisting of a ridge-type optical waveguide structure on a thin LiNbO3 substrate. Our fabrication technique achieves a drastic extension of the modulator's bandwidth and a reduction of half-wave voltage. Demonstration of 90-Gbaud NRZ-DP-DQPSK signal generation with the modulator successfully achieved a bit rate of 360-Gb/s under full-ETDM configuration.

DV-Hop algorithm produces errors in location estimations due to inaccurate hop size. We propose a novel localization scheme based on DV-Hop to improve positioning accuracy with least error hop sizes of anchors and average hop sizes of unknowns. The least error hop size of an anchor minimizes its location error, but it may be far small or large. To cope with this inconsistent hop size, each unknown node calculates its average hop size with hop sizes from anchors. Simulation results show that the proposed algorithm outperforms the DV-Hop algorithm in location estimations.

We present the recovery of 2.5 Gb/s synchronous 16-point quadrature amplitude modulation data in real-time for an linewidth-times-symbol-duration ratio of 0.00048 after transmission over 1.6 km standard single mode fiber.

Since retina blood vessels (RBV) are a major factor in ophthalmological diagnosis, it is essential to detect RBV from a fundus image. In this letter, we proposed the detection method of RBV using a morphological analysis and support vector machine classification. The proposed RBV detection method consists of three strategies: pre-processing, features extraction and classification. In pre-processing, noises were reduced and RBV were enhanced by anisotropic diffusion filtering and illumination equalization. Features were extracted by using the image intensity and morphology of RBV. And a support vector machine (SVM) classification algorithm was used to detect RBV. The proposed RBV detection method was simulated and validated by using the DRIVE database. The averages of accuracy and TPR are 0.94 and 0.78, respectively. Moreover, by comparison, we confirmed that the proposed RBV detection method detected RBV better than the recent RBV detections methods.

An unsupervised algorithm is proposed for learning overcomplete topographic representations of nature image. Our method is based on Independent Component Analysis (ICA) model due to its superiority on feature extraction, and overcomes the weakness of traditional method in fast overcomplete learning. Besides, the learnt topographic representation, resembling receptive fields of complex cells, can be used as descriptors to extract invariant features. Recognition experiments on Caltech-101 dataset confirm that these complex cell descriptors are not only efficient in feature extraction but achieve comparable performances to traditional descriptors.

The development of the electricity market enables us to provide electricity of varied quality and price in order to fulfill power consumers' needs. Such customers choices should influence the process of adjusting power generation and spinning reserve, and, as a result, change the structure of a unit commitment optimization problem (UCP). To build a unit commitment model that considers customer choices, we employ fuzzy variables in this study to better characterize customer requirements and forecasted future power loads. To measure system reliability and determine the schedule of real power generation and spinning reserve, fuzzy Value-at-Risk (VaR) is utilized in building the model, which evaluates the peak values of power demands under given confidence levels. Based on the information obtained using fuzzy VaR, we proposed a heuristic algorithm called local convergence-averse binary particle swarm optimization (LCA-PSO) to solve the UCP. The proposed model and algorithm are used to analyze several test systems. Comparisons between the proposed algorithm and the conventional approaches show that the LCA-PSO performs better in finding the optimal solutions.

This paper provides conceptual and experimental analysis of a new approach in the study of kanji, our “Learner's Visualization (LV) Approach”. In a previous study we found that the LV Approach assists beginning learners in significantly updating their personal kanji deconstruction visualization. Additionally, in another study our findings provided evidence that beginning learners also receive a significant impact in the ability to acquire vocabulary. In this study, our research problem examines how beginning and intermediate students use visualization to cognitively deconstruct (divide) kanji in different ways, and how this affects their learning progress. We analyze the cognitive differences in how kanji learners explore and deconstruct novel kanji while using the LV Approach and how these differences affect their learning process while using the LV Approach. During the learning experience, our LILES System (Learner's Introspective Latent Envisionment System), based on the LV Approach, guides learners to choose from a set of possible “kanji deconstruction layouts” (layouts showing different ways in which a given kanji can be divided). The system then assists learners in updating their “kanji deconstruction level” (the average number of parts they visualize within kanji according to their current abilities). Statistical analysis based on achieved performance was conducted. The analysis of our results proves that there are cognitive differences: beginners deconstruct kanji into more parts (“blocks”) than intermediate learners do, and while both improve their kanji deconstruction scores, there is a more significant change in “kanji deconstruction level” in beginners. However, it was also found that intermediate learners benefit more in “kanji retention score” compared with beginners. Suggestions for further research are provided.