Regarding IP-based video applications over wireless networks, the multi-layer header overhead may significantly affect the estimation of target video encoding bit rate and the effective throughput of wireless network. Based on the existing header structure of video packets, this study intends to deal with the header overhead problem from the end-to-end viewpoint. This paper first proposes a simple yet robust closed-form that can determine accurately and timely the optimal video payload length at the video sender based on the current wireless channel condition. The contribution can effectively improve the WLAN throughput and enhance the error resilience effect of scalable video data simultaneously. This study further explores the impact of multi-layer header overhead to the video coding work and proposes a Dynamic Header Overhead Accommodation (DHOA) scheme, which is executed in the video compression layer, to adjust dynamically the available video encoding bits for accommodating the header overhead in advance. The contributions of this paper are robust for various IP implementations such as IPSec (IP Security) over different 802.11 standards. Analytical and simulation results verify the accuracy and effectiveness of the proposed closed-form and header accommodation method. Using DHOA, the bandwidth mismatch between the actual bandwidth demand of packetized video data and the available network bandwidth is no more than 1.1% regardless of the packet sizes used in this paper.

The RGB signals generated by different cameras are not equal for the same scene. Therefore, cameras are characterized based on a CIE standard colorimetric observer. One method of deriving a colorimetric characterization matrix between camera RGB output signals and CIE XYZ tristimulus values is least squares polynomial modeling. Yet, this involves tedious experiments to obtain a camera transfer matrix under various white balance points for the same camera. Accordingly, the current paper proposes a new method for obtaining camera transfer matrices under different white balances using a 33 camera transfer matrix under a specific white balance point.

A block-matching-based self-organizing map (BMSOM) is presented. Finding a winner is carried out for each block, which is a set of neurons arranged in square. The proposed learning process updates the reference vectors of all of the neurons in a winner block. Then, the degrees of vector modifications are mainly controlled by the size (i.e., the number of neurons) of the winner block. To prevent a single cluster with neurons from splitting into some disjointed clusters, the restriction of the block size is imposed in the beginning of learning. At the main stage, this restriction is canceled. In BMSOM learning, the size of a winner block does not always decrease monotonically. The formula used to update the reference vectors is basically uncontrolled by time. Therefore, even if a map is in a nonstationary environment, training the map is probably pursued without interruption to adjust time-controlled parameters such as learning rate. Numerical results demonstrate that the BMSOM makes it possible to improve the plasticity of maps in a nonstationary environment and incremental learning.

This letter develops convergence analysis of normalized sign-sign algorithm (NSSA) for FIR-type adaptive filters, based on an assumption that filter tap weights are Gaussian distributed. We derive a set of difference equations for theoretically calculating transient behavior of filter convergence, when the filter input is a White & Gaussian process. For a colored Gaussian input and a large number of tap weights, approximate difference equations are also proposed. Experiment with simulations and theoretical calculations of filter convergence demonstrates good agreement between simulations and theory, proving the validity of the analysis.

A supervisor proposed by Ramadge and Wonham controls a discrete event system (DES) so as to satisfy logical control specifications. However a precise description of both the specifications and the DES is needed for the control. This paper proposes a synthesis method of the supervisor for decentralized DESs based on reinforcement learning. In decentralized DESs, several local supervisors exist and control the DES jointly. Costs for disabling and occurrence of events as well as control specifications are considered. By using reinforcement learning, the proposed method is applicable under imprecise specifications and uncertain environment.

This paper considers the low-frequency scattering by a circular dielectric cylinder and modifies the exact polarizability tensor to extend the valid region of the known low-frequency solution. When compared to the traditional formulation, the proposed solution is shown to be valid for cylinders with a higher dielectric constant and larger radius.

In this paper, we present a new all-digital carrier recovery loop for high-order quadrature amplitude modulation (QAM) signal constellations. The proposed approach is a blind phase-frequency detector structure that consists of a phase detector, a phase offset estimator, a frequency offset estimator, and a digital control oscillator. Compared to previous related approaches, the proposed algorithm provides a wider acquisition range and a more accurate estimation of frequency and phase offsets. These features are demonstrated by simulation results of the DOCSIS (Data-Over-Cable Service Interface Specifications) cable modem system.

The conventional decentralized supervisory control architectures for discrete event systems assume that default control of controllable events is static. In this paper, we propose a new decentralized supervisory control architecture using dynamic default control of controllable events. We present necessary and sufficient conditions for the existence of a decentralized supervisor in the proposed architecture. Then, we give an example of a language that is achieved in the proposed architecture, but not in the conventional architectures using static default control.

To take intercarrier interference (ICI) attributed to time variations of the channel into consideration, the time- and frequency-selective (doubly-selective) channel is parameterized by a finite parameter model. By capitalizing on the finite parameter model to approximate the doubly-selective channel, a Kalman filter is developed for channel estimation. The ICI suppressing, reduced-complexity Viterbi-type Maximum Likelihood (RML) equalizer is incorporated into the Kalman filter for recursive channel tracking and equalization to improve the system performance. An enhancement in the channel tracking ability is validated by theoretical analysis, and a significant improvement in BER performance using the channel estimates obtained by the recursive channel estimation method is verified by Monte-Carlo simulations.

In order to simultaneously combat both of the inter-carrier interferences (ICIs) and multiple access interferences (MAIs) to achieve reliable performance in multi-carrier code division multiple access (MC-CDMA) systems, this letter proposes a maximum likelihood based scheme for joint frequency offset estimation and multiuser symbol detection. To reduce the computational complexity called for by the joint decision statistic without extra mechanisms, the genetic algorithm (GA) is employed to solve the nonlinear optimization involved. Due to the robustness of the GA, the joint decision statistic can be efficiently solved, and, as shown by furnished simulation results, the proposed approach can offer satisfactory performance in various scenarios.

This paper addresses the parameter estimation problem of an interval-based hybrid dynamical system (interval system). The interval system has a two-layer architecture that comprises a finite state automaton and multiple linear dynamical systems. The automaton controls the activation timing of the dynamical systems based on a stochastic transition model between intervals. Thus, the interval system can generate and analyze complex multivariate sequences that consist of temporal regimes of dynamic primitives. Although the interval system is a powerful model to represent human behaviors such as gestures and facial expressions, the learning process has a paradoxical nature: temporal segmentation of primitives and identification of constituent dynamical systems need to be solved simultaneously. To overcome this problem, we propose a multiphase parameter estimation method that consists of a bottom-up clustering phase of linear dynamical systems and a refinement phase of all the system parameters. Experimental results show the method can organize hidden dynamical systems behind the training data and refine the system parameters successfully.

A polarization-independent liquid crystal (LC) grating with a microscale LC molecular alignment pattern is proposed. The microscale LC alignment pattern is achieved using a microrubbing technique. The optical properties of the proposed LC grating are theoretically discussed in detail using Jones matrix method. Optimum condition for obtaining maximum +1st or -1st diffraction efficiencies is derived. The diffraction efficiency of the LC grating is measured and the diffraction efficiency characteristics are compared with the theoretical result. Furthermore, the dependence of the polarization direction of the incident light on the diffraction efficiency is discussed.

The next-generation wireless networks will bring users with Software Defined Radio (SDR) terminals seamless mobility and ubiquitous computing through heterogeneous networks. This paper proposes a soft-prioritization based system selection algorithm performed by SDR terminal and investigates the effectiveness of the soft-prioritization based system selection by using a concrete simulation model. To maximize the quality of service (QoS), wireless communication systems are prioritized on the basis of criteria for system selection such as data rate, channel quality and cost, and should be dynamically changed. However, frequent inter-system handovers based on hard-prioritization are undesirable in view of interrupting and dropping, particularly for real-time traffic and managing channel capacities. Wireless communication systems are softly prioritized in the soft-prioritization based system selection algorithm, and therefore inter-system handovers between systems with the same priority aren't initiated. To elucidate the validity of the soft-prioritization based system selection algorithm, a system simulation model consisting of five wireless communication systems is employed. Simulation results confirm that the soft-prioritization system selection algorithm offers higher performance in terms of the number of inter-system handovers and throughput of best effort traffic.

Driving methods for TFT-OLEDs are explained with their features and classified from the viewpoints of grayscale methods and uniformizing methods. This classification leads us to a novel proposal using time ratio grayscale and current uniformization. This driving method maintains current uniformity and simultaneously overcomes charging shortage of the pixel circuit for low grayscale levels and current variation due to the shift of operating points. Tolerance toward degraded characteristics, linearity of grayscale and luminance uniformity against degraded characteristics are confirmed using circuit simulation.

Volume Graphics Clusters (VG Clusters) have proven to be efficient in a wide range of visualization applications and have also shown promise in some other applications where the image composition device could be fully utilized. The main differentiating feature from other graphics clusters is a specialized image composition device, commercially available as the MPC Image Compositor, which enables the building of do-it-yourself VG Clusters. Although this device is highly scalable, the unidirectional composition flow limits the data subdivision to the quantity of physically available rendering nodes. In addition, the limited buffer memory limits the maximum capable image composition size, therefore limiting its use in large-scale data visualization and high-resolution visualization. To overcome these limitations, we propose and evaluate an image composition mechanism in which additional hardware is used for assisting the image composition process. Because of the synergistic use of two distinct image composition hardware devices we named it "Hybrid Image Composition". Some encouraging results were obtained showing the effectiveness of this solution in improving the VG Cluster 's potential. A low-cost parallel port based hardware barrier is also presented as an efficient method for further enhancing this kind of small-scale VG Cluster. Moreover, this solution has proven to be especially useful in clusters built using low-speed networks, such as Fast Ethernet, which are still in common use.

Eye contact is an effective means of controlling human communication, such as in starting communication. It seems that we can make eye contact if we simply look at each other. However, this alone does not establish eye contact. Both parties also need to be aware of being watched by the other. We propose a method of bidirectional eye contact satisfying these conditions for human-robot communication. When a human wants to start communication with a robot, he/she watches the robot. If it finds a human looking at it, the robot turns to him/her, changing its facial expressions to let him/her know its awareness of his/her gaze. When the robot wants to initiate communication with a particular person, it moves its body and face toward him/her and changes its facial expressions to make the person notice its gaze. We show several experimental results to prove the effectiveness of this method. Moreover, we present a robot that can recognize hand gestures after making eye contact with the human to show the usefulness of eye contact as a means of controlling communication.

A rack-mounted DC power-supply system utilizing Li-ion batteries, which have higher energy density than conventional VRLA batteries, was developed. The system was designed to have the management functions of Li-ion batteries, such as overcharge protection, over-discharge protection, and cell-voltage equalization, by taking operational requirements into consideration. The volume and weight of the entire system were decreased to one-fourth and three-fifths, respectively, of the volume and weight of a conventional system, making the proposed system ideal as a high-energy-density backup power supply. The functions, system configuration, and characteristics of this rack-mounted DC power supply system utilizing Li-ion batteries are described.

In this paper, we address how to efficiently support differentiated services with the optimized bandwidth reservation in a polling-based generalized TDMA network like E-PON (Ethernet Passive Optical Network). In E-PON, performances of service differentiation for QoS (Quality of Service) guaranteed multiples services are directly affected by the bandwidth reservation algorithm of ONU (Optical Network Unit) in addition to the priority-based packet scheduling. Our proposed Service Quality Pre-engagement (SQP) algorithm reduces the system buffer size, the light-load penalty problem and the service interference among classes effectively by partially introducing the dynamic forward recurrence reservation scheme for QoS guaranteed classes. We also introduce the FRC(Forward Reservation Class) Selection algorithm that preserves the optimized reservation bandwidth to minimize the unnecessary reservation contentions. These algorithms do not mandate the basic concept of DBA and request the similar amount of REPORT bandwidth. The analytic and simulation results are performed to evaluate the performances of the proposed algorithms.

In this paper the spectral density of the additive jitter noise in continuous time (CT) Delta-Sigma modulators (DSM) is derived analytically. Making use of the analytic results, extracted in this paper, a novel method for elimination of the damaging effects of the clock jitter in continuous time Delta-Sigma modulators is proposed. In this method instead of the conventional waveforms used in the feedback path of CT DSM's such as the non return to-zero, the return to-zero, and the half delay return to-zero, an impulse waveform is employed.

The requirement for achieving the smoothness of mode transit between track seeking and track following has become a challenging issue for hard disk drive (HDD) motion control. In this paper, a random-optimization-based self-organizing neuro-fuzzy controller (RO-SNFC) for HDD servo system is presented. The proposed controller is composed of three designs. First, the concept of pseudo-errors is used to detect the potential dynamics of the unknown plant for rule extraction. Second, the propensity of the obtained pseudo-errors is specified by a cubic regression model, with which the cluster-based self-organization is implemented to generate clusters. The generated clusters are regarded as the antecedents of the T-S fuzzy "IF-THEN" rules. The initial knowledge base of the RO-SNFC is established. Third, the well-known random optimization (RO) algorithm is used to evolve the controller parameters for control efficiency and robustness. In this paper, a motion reference curve for HDD read/write head is employed. With the reference velocity curve, the RO-SNFC is used to achieve the optimal positioning control. From the illustrations, the feasibility of the proposed approach for HDD servo systems is demonstrated. Through the comparison to other approaches, the excellent performance by the proposed approach in access time and positioning smoothness is observed.