The objective of this paper is to propose the Pulse Position Modulation (PPM) system which embeds the synchronizing signal in the information frame. In the proposed system, the frame for transmitting information is also the frame for acquiring frame timing. The data transmission rate of the proposed system is independent of the length of the synchronization signal because the proposed system does not require the synchronization frame. The data transmission rate and the synchronization performance for the proposed system are better than those of the conventional system.

In this paper, we propose a robust timing synchronization algorithm for wireless MAN OFDM systems. The proposed algorithm is composed of frame synchronization and FFT timing synchronization. The conventional correlation scheme for estimation of timing offset has an ambiguity in the detection of accurate symbol timing. The proposed scheme, however, shows a clear peak at the correct timing by using the conjugate-symmetric characteristic of preamble and is able to control the FFT window position continuously with the 1-st order loop filter. Simulation results demonstrate the superiority of the proposed algorithm.

In this paper, the confinement loss of octagonal photonic crystal fibers (PCFs) with an isosceles triangle lattice of air-holes are numerically investigated. Taking into account the confinement loss, the mode field diameter (MFD), the effective area (Aeff) and the chromatic dispersion of octagonal PCFs are calculated, compared to conventional hexagonal PCFs. It is found from confinement loss and MFD results that the octagonal PCFs can confine the field strongly than the hexagonal PCFs due to the different air filling fraction. Moreover, it is shown that the octagonal PCFs are obtained not only positive but also negative larger dispersion values and smaller Aeff values compared to the hexagonal PCFs.

In this paper, we develop a new distributed adaptive power control framework for multi-cell OFDM systems based on the game theory. A specific utility function is defined considering the users' achieved average utility per power, i.e., power unit based utility. We solve the subcarrier allocation issue naturally as well as the power control. Each user tries to maximize its utility by adjusting the transmit power on each subcarrier. A Nash equilibrium for the game is shown to exist and the numerical results show that our proposal outperforms the pure water-filling algorithm in terms of efficiency and fairness.

The delay characteristics of the MPsLS, a data forwarding scheme used for a core area of the integrated data service network, are discussed and analyzed. MPsLS has the capability of guaranteeing QoS on the per-flow level for time-sensitive applications and simultaneously maintaining the high utilization of network resources. In the MPsLS core area, the forwarding process is implemented with a fine-grain slot synchronization model, and at the ingress edge nodes, the forwarding process is carried with a coarse-grain frame synchronization model. The delay analyses are done according to three service models: the exact synchronization model, the less strict synchronization model for the appointed channels, and an asynchronous model for the filler channels. The authors give estimation equations of mean delay between edge-to-edge nodes in an MPsLS network, and introduce an effective method to determine the reserved bandwidth for given application flows based on numerical calculations from those theory analysis and simple simulation results.

Recently, researches and developments for measuring and modeling of the human body have been receiving much attention. Our aim is to reconstruct an accurate shape of a human foot from multiple camera images, which can capture dynamic behavior of the object. In this paper, a foot-shape database is used for accurate reconstruction of human foot. By using Principal Component Analysis, the foot shape can be represented with new meaningful variables. The dimensionality of the data is also reduced. Thus, the shape of object can be recovered efficiently, even though the object is partially occluded in some input views. To demonstrate the proposed method, two kinds of experiments are presented: reconstruction of human foot in a virtual reality environment with CG multi-camera images, and in real world with eight CCD cameras. In the experiments, the reconstructed shape error with our method is around 2 mm in average, while the error is more than 4 mm with conventional volume intersection method.

Combined input-crosspoint buffered (CICB) switches relax arbitration timing and provide high-performance switching for packet switches with high-speed ports. It has been shown that these switches, with one-cell crosspoint buffer and round-robin arbitration at input and output ports, provide 100% throughput under uniform traffic. However, under admissible traffic patterns with nonuniform distributions, only weight-based selection schemes are reported to provide high throughput. This paper proposes a round-robin based arbitration scheme for a CICB packet switch that provides 100% throughput for several admissible traffic patterns, including those with uniform and nonuniform distributions, using one-cell crosspoint buffers and no speedup. The presented scheme uses adaptable-size frames, where the frame size is determined by the traffic load.

This paper deals with graph colouring games, an example of pseudo-telepathy, in which two players can convince a verifier that a graph G is c-colourable where c is less than the chromatic number of the graph. They win the game if they convince the verifier. It is known that the players cannot win if they share only classical information, but they can win in some cases by sharing entanglement. The smallest known graph where the players win in the quantum setting, but not in the classical setting, was found by Galliard, Tapp and Wolf and has 32,768 vertices. It is a connected component of the Hadamard graph GN with N=c=16. Their protocol applies only to Hadamard graphs where N is a power of 2. We propose a protocol that applies to all Hadamard graphs. Combined with a result of Frankl, this shows that the players can win on any induced subgraph of G12 having 1609 vertices, with c=12. Moreover combined with a result of Godsil and Newman, our result shows that all Hadamard graphs GN (N ≥ 12) and c=N yield pseudo-telepathy games.

Framework technology is one of the promising approaches to reuse effectively software and its key issues are 1) to select the suitable frameworks for the software requirements specification, and 2) to fill the suitable hot spots with application-specific codes (customization). This paper proposes a new technique for automated support of the above issues by using labeled transition systems (LTSs) together with metrics technique. We model the behavior of the frameworks and the system behavior specified in the requirements specification by using two LTSs respectively. By establishing bisimilar relationship between the two LTSs, we check whether the behavior of the framework can match to the requirements and explore how to fill its hot spots. This process is done by means of constructing a graph to extract the bisimilar relationships, and each path of the graph denotes one of the implementations of the requirements by the framework. We attach some measures to the LTS of the framework, such as the number of the hot spots to be filled and the number of the parameters to be set up when filling the corresponding hot spot. These measures are used to estimate developer's efforts in filling the hot spots for each implementation, i.e. for each path of the graph. The result of estimating the efforts guides the developers to select the implementation, and the structure of the application-specific codes to be filled in can be automatically generated from the selected implementation. Furthermore we discuss case studies in the area of Web application, where Struts and Turbine can be used.

The speech noise reduction system based on the frequency domain adaptive line enhancer using a windowed modified DFT (MDFT) pair is presented. The adaptive line enhancer (ALE) is effective for extracting sinusoidal signals blurred by a broadband noise. In addition, it utilizes only one microphone. Therefore, it is suitable for the realization of speech noise reduction in portable electronic devices. In the ALE, an input signal is generated by delaying a desired signal using the decorrelation parameter, which makes the noise in the input signal decorrelated with that in the desired one. In the present paper, we propose to set decorrelation parameters in the frequency domain and adjust them to optimal values according to the relationship between speech and noise. Such frequency domain decorrelation parameters enable the reduction of the computational complexity of the proposed system. Also, we introduce the window function into MDFT for suppressing spectral leakage. The performance of the proposed noise reduction system is examined through computer simulations.

In this paper, we propose a distributed speaker recognition method using a nonparametric speaker model and Earth Mover's Distance (EMD). In distributed speaker recognition, the quantized feature vectors are sent to a server. The Gaussian mixture model (GMM), the traditional method used for speaker recognition, is trained using the maximum likelihood approach. However, it is difficult to fit continuous density functions to quantized data. To overcome this problem, the proposed method represents each speaker model with a speaker-dependent VQ code histogram designed by registered feature vectors and directly calculates the distance between the histograms of speaker models and testing quantized feature vectors. To measure the distance between each speaker model and testing data, we use EMD which can calculate the distance between histograms with different bins. We conducted text-independent speaker identification experiments using the proposed method. Compared to results using the traditional GMM, the proposed method yielded relative error reductions of 32% for quantized data.

In unidentifiable models, the Bayes estimation has the advantage of generalization performance over the maximum likelihood estimation. However, accurate approximation of the posterior distribution requires huge computational costs. In this paper, we consider an alternative approximation method, which we call a subspace Bayes approach. A subspace Bayes approach is an empirical Bayes approach where a part of the parameters are regarded as hyperparameters. Consequently, in some three-layer models, this approach requires much less computational costs than Markov chain Monte Carlo methods. We show that, in three-layer linear neural networks, a subspace Bayes approach is asymptotically equivalent to a positive-part James-Stein type shrinkage estimation, and theoretically clarify its generalization error and training error. We also discuss the domination over the maximum likelihood estimation and the relation to the variational Bayes approach.

This letter proposes an orthogonal frequency division multiplexing (OFDM) frame synchronization scheme when the guard interval (GI) consists of a zero-padded (ZP) sequence. The frame synchronization method uses the ZP symbol where nothing is transmitted for GI so that the drop in received power can be detected to find the beginning of the frame. Simulations reveal that this method significantly improves synchronization performance of the ZP-OFDM system in a multipath fading channel.

Modern digital systems design requires us to explore a large and complex design space to find a best configuration which satisfies design requirements. Such exploration requires a sound representation of design space from which design candidates are efficiently generated, each of which then is evaluated. This paper proposes a plan-generation-evaluation framework which supports a complete process of such design space exploration. The plan phase constitutes a design space of all possible design alternatives by means of a formally defined representation scheme of attributed AND-OR graph. The generation phase generates a set of candidates by algorithmic pruning of the design space in an attributed AND-OR graph with respect to design requirements as well as architectural constraints. Finally, the evaluation phase measures performance of design candidates in a pruned graph to select a best one. A complete process of cache design is exemplified to show the effectiveness of the proposed framework.

We introduce a robust classification method based on the Bayesian predictive distribution (Bayesian Predictive Classification, referred to as BPC) for speech recognition. We and others have recently proposed a total Bayesian framework named Variational Bayesian Estimation and Clustering for speech recognition (VBEC). VBEC includes the practical computation of approximate posterior distributions that are essential for BPC, based on variational Bayes (VB). BPC using VB posterior distributions (VB-BPC) provides an analytical solution for the predictive distribution as the Student's t-distribution, which can mitigate the over-training effects by marginalizing the model parameters of an output distribution. We address the sparse data problem in speech recognition, and show experimentally that VB-BPC is robust against data sparseness.

Over the last decade, the Bayesian approach has increased in popularity in many application areas. It uses a probabilistic framework which encodes our beliefs or actions in situations of uncertainty. Information from several models can also be combined based on the Bayesian framework to achieve better inference and to better account for modeling uncertainty. The approach we adopted here is to utilize the benefits of the Bayesian framework to improve acoustic model precision in speech recognition systems, which modeling a wider-than-triphone context by approximating it using several less context-dependent models. Such a composition was developed in order to avoid the crucial problem of limited training data and to reduce the model complexity. To enhance the model reliability due to unseen contexts and limited training data, flooring and smoothing techniques are applied. Experimental results show that the proposed Bayesian pentaphone model improves word accuracy in comparison with the standard triphone model.

This paper proposes novel methods to provide intelligence for characters in fighting action games by using neural networks. First, how a character learns basic game rules and matches against randomly acting opponents is considered. Since each action takes more than one time unit in general fighting action games, the results of a character's action are exposed not immediately but several time units later. We evaluate the fitness of a decision by using the relative score change caused by the decision. Whenever the scores of fighting characters are changed, the decision causing the score change is identified, and then the neural network is trained by using the score difference and the previous input and output values which induced the decision. Second, how to cope more properly with opponents that act with predefined action patterns is addressed. The opponents' past actions are utilized to find out the optimal counter-actions for the patterns. Lastly, a method in order to learn moving actions is proposed. To evaluate the performance of the proposed algorithm, we implement a simple fighting action game. Then the proposed intelligent character (IC) fights with the opponent characters (OCs) which act randomly or with predefined action patterns. The results show that the IC understands the game rules and finds out the optimal counter-actions for the opponents' action patterns by itself.

To simultaneously support guaranteed real-time services and best-effort service, a Priority-based Scheduling Architecture (PSA) designed for high-speed switches is proposed. PSA divides packet scheduling into high-priority phase and low-priority phase. In the high-priority phase, an improved sorted-priority algorithm is presented. It introduces a new constraint into the scheduling discipline to overcome bandwidth preemption. Meanwhile, the virtual time function with a control factor α is employed. Both computer simulation results and theoretic analysis show that the PSA mechanism has excellent performance in terms of the implementation complexity, fairness and delay properties.

H.264 video coding standard has a significant performance better than the other standards are the adoption of variable block sizes, multiple reference frames, and the consideration of rate distortion optimization within the codec. However, these features incur a considerable complexity in the encoder for motion estimation. As for the multiple reference frames motion estimation, the increased computation is in proportion to the number of searched reference frames. In this paper, a fast multiple frame reference frames selection method is proposed for H.264 video coding. The proposed algorithm can efficiently determine the best reference frame from the allowed five reference frames. As determine the number of reference frames to search the motion using the correlation of the different block between the block of current frame and that of previous frame, this scheme can efficiently reduce the computational cost while keeping the similar quality and bit-rate. Simulation results show that the speed of the proposed method is faster than that of the original scheme adapted in JVT reference software JM95 while keeping the similar video quality and bit-rate.

New service concepts involving mobile devices with a diverse range of embedded sensors are emerging that share contexts supporting communication on a wireless network infrastructure. To promote these services in mobile devices, we propose a method that can efficiently detect a context provider by partitioning the location, time, speed, and discovery sensitivities.