Prediction of actual symbol probability is crucial for statistical data compression that uses arithmetic coder. Krichevsky-Trofimov (KT) estimator has been a standard predictor and applied in CTW or FWCTW methods. However, KT-estimator performs poorly when non occurring symbols appear. To rectify this we proposed a zero-redundancy estimator, especially with a finite window(Rashid and Kawabata, ISIT2003) for non stationary source. In this paper, we analyze the zero-redundancy estimators in the case of Markovian source and give an asymptotic evaluation of the redundancy. We show that one of the estimators has the per symbol redundancy given by one half of the dimension of positive parameters divided by the window size when the window size is large.

This paper clarifies a necessary condition and a sufficient condition for transmissibility for a given set of general sources and a given general broadcast channel. The approach is based on the information-spectrum methods introduced by Han and Verdu. Moreover, we consider the capacity region of the general broadcast channel with arbitrarily fixed error probabilities if we send independent private and common messages over the channel. Furthermore, we treat the capacity region for mixed broadcast channel.

The bandwidth explosion ushered in by the popularity of the Internet has spurred the recent acceleration in the development and deployment of equipment supporting packet based broadband services. This coupled with the widespread deployment of WDM based Optical Transport Systems in the core network to satisfy the corresponding increase in capacity demand, has led network planners for tighter coordination between IP and Optical layers to increase reliability, robustness of next generation backbone network. In this paper, we propose a solution known as border model, which is tailored to address deployment concerns associated with GMPLS technology in existing networks. We extend our proposal to include, "Border model based Multi-layer service network architecture," to provide coordinated multi-layer IP and Optical services, for different network design scenarios. Resource Control is an important aspect of multi-layer service networks. This paper examines next generation requirements for resource control, defines resource control architecture and presents some evaluation results for multi-layer recovery techniques in the context of Multi-layer service network based on border model.

We show that distributed source coding of multi-view images in camera sensor networks (CSNs) using adaptive modules can come close to the Slepian-Wolf bound. In a systematic scenario with limited node abilities, work by Slepian and Wolf suggest that it is possible to encode statistically dependent signals in a distributed manner to the same rate as with a system where the signals are jointly encoded. We considered three nodes (PN, CN and CNs), which are statistically depended. Different distributed architecture solutions are proposed based on a parent node and child node framework. A PN sends the whole image whereas a CNs/CN only partially, using an adaptive coding based on adaptive module-operation at a rate close to theoretical bound - H(CNs|PN)/H(CN|PN,CNs). CNs sends sub-sampled image and encodes the rest of image, however CN encodes all image. In other words, the proposed scheme allows independent encoding and jointly decoding of views. Experimental results show performance close to the information-theoretic limit. Furthermore, good performance of the proposed architecture with adaptive scheme shows significant improvement over previous work.

We present an efficient method to optimize network resource allocations under nonlinear Quality of Service (QoS) constraints. We first propose a suite of generalized proportional allocation schemes that can be obtained by minimizing the information-theoretic function of relative entropy. We then optimize over the allocation parameters, which are usually design variables an engineer can directly vary, either for a particular user or for the worst-case user, under constraints that lower bound the allocated resources for all other users. Despite the nonlinearity in the objective and constraints, we show this suite of resource allocation optimization can be efficiently solved for global optimality through a convex optimization technique called geometric programming. This general method and its extensions are applicable to a wide array of resource allocation problems, including processor sharing, congestion control, admission control, and wireless network power control.

The resource allocation problem in multi-agent systems is one of the crucial problems hindering the development of multi-agent technologies. This study demonstrates that "time delay" functions as an effective factor in a resource allocation, contrasting to the conventional real-time oriented multi-agent paradigm by 1) introducing a "fickle" agent, whose own strategy fluctuates randomly, and 2) an agent repository mechanism. This study also demonstrates that in the resource allocation process, time delay induces dramatic changes in performance, the specific phenomenon is the so-called "phase transition phenomenon". This finding means emergence of the phase transition is cited as a major factor governing multi-agent system performance. This knowledge is of essential importance in the regulation in multi-agent performance.

The explicit construction of a universal source code for correlated sources is presented. The construction is based on a technique of simulated random coding algorithms [5]. The proposed algorithm simulates the random generation of linear codes. For every pair of correlated sources whose achievable rate region includes a given pair of encoding rates, the decoding error rate of the proposed algorithm goes to zero almost surely as the block length goes to infinity.

We propose a new two-stage blind separation and deconvolution strategy for multiple-input multiple-output (MIMO)-FIR systems driven by colored sound sources, in which single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. After the separation by the SIMO-ICA, a blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated and the mixing system has a nonminimum phase property. The simulation results reveal that the proposed algorithm can successfully achieve separation and deconvolution of a convolutive mixture of speech, and outperforms a number of conventional ICA-based BSD methods.

This paper proposes near-field sound-source localization based on crosscorrelation of a signed binary code. The signed binary code eliminates multibit signal processing for simpler implementation. Explicit formulae with near-field assumption are derived for a two microphone scenario and extended to a three microphone case with front-rear discrimination. Adaptive threshold for enabling and disabling source localization is developed for robustness in noisy environment. The proposed sound-source localization algorithm is implemented on a fixed-point DSP. Evaluation results in a robot scenario demonstrate that near-field assumption and front-rear discrimination provides almost 40% improvement in DOA estimation. A correct detection rate of 85% is obtained by a robot in a home environment.

A compensation method of the array element pattern is proposed to measure EM field distribution on an observation plane located several wavelengths away from electronic devices in a short time. Numerical and experimental data of the 3 and 5 element collinear dipole array sensors are presented to demonstrate the validity of the proposed method.

This paper proposes resource management in Layer 1 Virtual Private Networks (VPNs). We have been proposing Layer 1 VPNs that provide layer 1 services to multiple customers over the single optical network with per VPN control and management capabilities. We have proposed two resource management models for Layer 1 VPNs, which constitute different class of services. One is the shared model, where resources are shared among VPNs. The other is the dedicated model, where resources are explicitly pre-assigned to each VPN. In this paper, after introducing an overview of Layer 1 VPNs, we evaluate several path computation algorithms for these two models focusing on the multi layer network scenario. In the shared model, there are several existing studies for non-VPN cases, but considerations for VPN cases are not investigated. This paper evaluates algorithms originally proposed for non-VPN cases for use in VPN cases. Simulation results show that the path computation algorithm that works as saving layer 1 resources achieves better resource sharing effect. In the dedicated model, the problem is identical to non-VPN cases. There is one conventional algorithm, but amount of available resources is not well considered. We propose a novel path computation algorithm. Simulation results show effectiveness of our proposed algorithm against the conventional algorithm. Furthermore, resource usage efficiency of two resource management models is compared. We analyze and propose applicability of resource management models.

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 visualization method of coherent source locations based on the Sampled Pattern Matching (SPM) method is described. Modified SPM method is proposed to improve the S/N, in which the measurement of the electric field distribution is repeated in appropriate time duration and eigenvalue decomposition of the covariance matrix is introduced. A combination of the modified SPM method with the Weighted Subspace Fitting (WSF) method is also proposed to estimate accurate source locations. A calibration technique by using a reference antenna to compensate the complex pattern of the receiving antenna is proposed. Experimental investigation to estimate source location for one dipole antenna and two dipole antennas is also made to demonstrate the validity of the proposed method.

Radio resource is the bottleneck for current multimedia wireless networks. Intelligent traffic control strategies can be enforced to optimize resource allocation so as to enhance network performance. In this study, dynamic control scheme for non-real-time traffic and autonomic control schemes for multimedia traffic are proposed to guarantee the required quality of service (QoS) in the inference-dominated high-speed wireless environment. Both handoff priority and terminal mobility are also taken into consideration. The performance of the state-dependent multidimensional birth-death process is derived by the efficient matrix-analytic methods (MAMs). Compared with the previous results, this paper shows that the proposed control methods can be used for both real-time and non-real-time multimedia traffic in order to meet the required performance without degrading the quality of multimedia services. These results are also important for the design of evolving multimedia wireless systems as well as network optimization.

This paper overviews a total solution for frequency-domain blind source separation (BSS) of convolutive mixtures of audio signals, especially speech. Frequency-domain BSS performs independent component analysis (ICA) in each frequency bin, and this is more efficient than time-domain BSS. We describe a sophisticated total solution for frequency-domain BSS, including permutation, scaling, circularity, and complex activation function solutions. Experimental results of 22, 33, 44, 68, and 22 (moving sources), (#sources#microphones) in a room are promising.

In this paper, an adaptive resource allocation scheme for video stream based on video stream character and user mobility in wireless LAN is proposed. The proposed adaptive allocation scheme allocates the time slots according to the kind of the real-time or non real-time video stream, the required bit rate of video stream and user's mobility by each user. In the proposed system, when user requests the non real-time video stream and its dwell time is smaller than the service time of the video source, more time slots are allocated to the user. When user requests the non real-time video stream and its dwell time is larger than the service time of the source video, or when user requests the real-time video stream, minimum amount of the required time slots are allocated. The computer simulation results show that the proposed allocation scheme can achieve the better performance than the conventional allocation schemes which allocate the time slots only considering the required bit rate or user's dwell time.

In this paper, we address the blind separation problem of binaural mixed signals, and we propose a novel blind separation method, in which a self-generator for initial filters of Single-Input-Multiple-Output-model-based independent component analysis (SIMO-ICA) is implemented. The original SIMO-ICA which has been proposed by the authors can separate mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Although this attractive feature of SIMO-ICA is beneficial to the binaural sound separation, the current SIMO-ICA has a serious drawback in its high sensitivity to the initial settings of the separation filter. In the proposed method, the self-generator for the initial filter functions as the preprocessor of SIMO-ICA, and thus it can provide a valid initial filter for SIMO-ICA. The self-generator is still a blind process because it mainly consists of a frequency-domain ICA (FDICA) part and the direction of arrival estimation part which is driven by the separated outputs of the FDICA. To evaluate its effectiveness, binaural sound separation experiments are carried out under a reverberant condition. The experimental results reveal that the separation performance of the proposed method is superior to those of conventional methods.

This paper focuses on the underdetermined blind source separation (BSS) of three speech signals mixed in a real environment from measurements provided by two sensors. To date, solutions to the underdetermined BSS problem have mainly been based on the assumption that the speech signals are sufficiently sparse. They involve designing binary masks that extract signals at time-frequency points where only one signal was assumed to exist. The major issue encountered in previous work relates to the occurrence of distortion, which affects a separated signal with loud musical noise. To overcome this problem, we propose combining sparseness with the use of an estimated mixing matrix. First, we use a geometrical approach to detect when only one source is active and to perform a preliminary separation with a time-frequency mask. This information is then used to estimate the mixing matrix, which allows us to improve our separation. Experimental results show that this combination of time-frequency mask and mixing matrix estimation provides separated signals of better quality (less distortion, less musical noise) than those extracted without using the estimated mixing matrix in reverberant conditions where the reverberant time (TR) was 130 ms and 200 ms. Furthermore, informal listening tests clearly show that musical noise is deeply lowered by the proposed method comparatively to the classical approaches.

This paper presents a distributed task assignment algorithm in a logical unidirectional ring, which guarantees that almost all tasks are assigned to servers with the first come first served (FCFS) policy without a global clock. A task assignment for a process is obtained in the time period needed for a message to circle the ring. This time period is almost optimal for a unidirectional ring. The FCFS policy is very important in terms of task fairness and can also avoid starvation and provide an efficient response time. Simulation results show that the algorithm generally works better than conventional task assignment or load balancing schemes with respect to both mean response time and task fairness.

Routing protocols are a critical component in IP networks. Among these, the Open Shortest Path First (OSPF) has been a widely used routing protocol in IP networks for some years. Beside dedicated hardware, a great interest on routing systems based on open software is raising among Internet Service Providers. Many open source implementations of this protocol have been developed, among which GNU Zebra is one of the most complete. In this paper we perform a study of the performances of the Shortest Path First computation in GNU Zebra, as prescribed by the Internet Engineering Task Force, and we provide a comparison between a Cisco 2621 access router and a PC-based router equipped with routing software GNU Zebra. Moreover we describe a set of modifications made on the GNU Zebra code in order to optimize some processes, whose algorithms were not efficient and whose experimental measures had showed a lack of optimization, thus finally obtaining performances better than the one measured on commercial systems.