This letter proposes an efficient method to find the optimum subfield code, which minimizes the visual artifacts on the motion pictures of the plasma display panel (PDP). Existing codes were constructed to reduce dynamic false contour (DFC) only, and they are fixed codes used for every image. In contrast, the proposed method aims to minimize the total artifacts by DFC and halftone noise (HN), and it finds the best code for a given image, dynamically. First, this letter presents the novel models to estimate the effect of DFC and HN for given codewords and a given image. Then, it presents an efficient method that finds the optimum code for a given image using the well-known shortest-path algorithm. Experimental results, using 459 HDTV images, illustrated that the proposed approach improved the average PSNR by 0.713 dB and 7.004 dB in DFC and HN, respectively, when compared with Gravity Centre Code [1].

An alternative human interface enabling the handicapped with severe motor disabilities to control an assistive system is presented. Since this interface relies on the biosignals originating from the contraction of muscles on the face during particular movements, even individuals with a paralyzed limb can use it with ease. For real-world application, a dedicated hardware module employing a general-purpose DSP was implemented and its validity tested on an electrically powered wheelchair. Furthermore, an additional attempt to reduce error rates to a minimum for stable operation was also made based on the entropy information inherent in the signals during the classification phase. In the experiments in which 11 subjects participated, it was found most of them could control the target system at their own will, and thus the proposed interface could be considered a potential alternative for the interaction of the severely handicapped with electronic systems.

The development of a small and multiband antenna plays an important role in the rapidly growing mobile communication market. This paper presents the design of a novel small and wideband planar inverted F-antenna which simultaneously covers GSM850/GSM900/DCS1900/IMT2000/WLAN/DMB services. The proposed antenna consists of a main patch with a pair of slits and L-shaped patch, occupying a total volume of 15366 mm3. A very wide impedance bandwidth characteristic was achieved by optimizing both the gap distance between the feed line and L-shaped patch, and also the lengths and widths of a pair of slits on the main patch, which is excited by the modified CPW-fed line. The average gains at the frequencies of 850, 2000 and 2600 MHz were -2.51, -1.42 and -1.68 dBi, respectively. The overall shape of the radiation patterns is suitable for mobile communications.

We demonstrate a fast shutdown and resumption of a logic circuit applied a nonvolatile latch having SrBi2(Ta,Nb)2O9 (SBT) capacitors without a higher drive voltage than a logic voltage of 1.8 V. By assigning an individual drive circuit of the SBT capacitors to the nonvolatile latch not sharing a drive circuit with multiple nonvolatile latches, the fast shutdown and resumption of a logic circuit were completed in 7.5 ns at a drive voltage of 1.3 V. The fast shutdown and resumption without an addition of a high drive voltage to a logic circuit meets a requirement from power-saving applications of system LSIs fabricated in CMOS technologies at 90-nm and below.

Fairness among uplink and downlink TCP flows can not be supported in infrastructure IEEE 802.11 Wireless LANs using the distributed coordination function (DCF). In order to resolve this problem, we propose the Distributed Access Time Control (DATC) scheme, in which each station controls the rates of its TCP flows based on channel access time. The DATC scheme can provide per-station fairness even when the number and direction of flows in each station are different. This scheme can be simply implemented in mobile stations without having to modify the access points. The properties of the proposed scheme are investigated and its effectiveness is verified through simulations.

Virtual Private Networks (VPNs) are overlay networks established on top of a public network backbone with the goal of providing a service comparable to Private Networks (PNs). The recently proposed VPN hose-model provides customers with flexible and convenient ways to specify their bandwidth requirements. To meet the specified bandwidth requirements, the Network Service Provider (NSP) must reserve sufficient bandwidth on the data transmission paths between each pair of endpoints in a VPN. In addition, the reliability of a VPN depends on the reliability of the data transmission paths. Italiano et al. proposed an algorithm that finds a set of backup paths for a given VPN (VPN tree) under the single-link failure model [1]. When a link failure is detected on a VPN tree, a backup path corresponding to the failed link can be activated to restore the disconnected VPN tree into a new one, thereby ensuring the reliability of the VPN. However, Italiano's algorithm cannot guarantee that the specified bandwidth requirement of the given VPN under the single-link failure model will be met. To address this issue, we propose a new backup path set selection algorithm called BANGUAD in this paper. In addition, the problem of establishing multiple bandwidth-guaranteed hose-model VPNs under the single-link failure model has not been investigated previously. However in this problem, bandwidth-sharing algorithms have the potential to improve the performance of a provisioning algorithm significantly. Therefore, we also propose a bandwidth sharing algorithm and three provisioning algorithms for establishing multiple bandwidth-guaranteed hose-model VPNs under the single-link failure model. Simulations that compare the performance of the proposed algorithms are reported.

In direct sequence code division multiple access (DS-CDMA), variable rate transmission can be realized by simply changing the spreading factor SF for the given chip rate. In a frequency-selective fading channel, the transmission performance can be improved by using rake combining. However, when a very low SF is used for achieving a high transmission rate, error floor is produced due to insufficient suppression of inter-chip interference (ICI). In this paper, decision feedback chip-level maximum likelihood detection (DF-CMLD) is proposed that can suppress the ICI. An upper-bound for the conditional bit error rate (BER) is theoretically derived for the given spreading sequence and path gains. The theoretical average BER performance is numerically evaluated by Monte-Carlo numerical computation using the derived conditional BER. The numerical computation results are confirmed by computer simulation of DS-CDMA signal transmission with DF-CMLD.

How to mitigate the influence of unfair testimonies remains an open issue in the research of rating systems. Methods have been proposed to filter the unfair testimonies in order to mitigate the influence of unfair testimonies. However, existing methods depend on assumptions that ratings follow a particular distribution to carry out the testimony filtering. This constrains them in specific rating systems and hinders their applications in other reputation systems. Moreover, existing methods do not scale well with the increase of testimony number due to their iterative nature. In this paper, a novel entropy-based method is proposed to measure the testimony quality, based on which unfair testimonies are further filtered. The proposed method does not require the assumption regarding the rating distribution. Moreover, it scales linearly with the increase of the testimony number. Experimental results show that the proposed method is effective in mitigating the influence of various types of unfair testimonies.

This paper studies the scattering of a TM plane wave from a perfectly conductive sinusoidal surface with finite extent by the small perturbation method. We obtain the first and second order perturbed solutions explicitly, in terms of which the differential scattering cross section and the total scattering cross section per unit surface are calculated and are illustrated in figures. By comparison with results by a numerical method, it is concluded that the perturbed solution is reasonable even for a critical angle of incidence if the surface is small in roughness and gentle in slope and if the corrugation width is less than certain value. A brief discussion is given on multiple scattering effects.

The optical network represents a promising approach to achieve a scalable backbone network. In backbone networks, survivability is important because high volumes of traffic are prone to be damaged by faulty equipment. Various design methods for survivable optical networks have been proposed, although none considering the simultaneous maintenance of multiple transmission lines has been proposed to our knowledge. This paper proposes a design method for survivable optical networks where multiple transmission lines sharing common transmission equipment may suffer simultaneous damage, due to failure in the transmission equipment. Moreover, two transmission lines can be maintained simultaneously. A mathematical programming model to obtain the optimum lightpath arrangement is presented assuming three kinds of lightpath recovery schemes. The relation between the required transmission line capacity and the combination pattern of two transmission lines that undergo maintenance is clarified using the proposed design method.

A probability density distribution of the envelope of maximal-ratio combiner output in a very generally distributed fading channel is derived. The derived formula has a series expanded form consisting of positive terms of the well-known m-distribution and is practical for numerical calculation, approximation and analysis.

In this paper an analysis of component and system reliability for lattice systems is proposed when component failures are not statistically independent. We deal the case that the failure rate of a component depends on the number of the adjacent failed components. And we discuss the maintainability of the system when a failed component is replaced by a spare component. At first we discuss the approximated reliability of each component. Then we estimate the mean number of failed components. Furthermore, the system reliability is approximated by using the component reliability.

Based on the theory of block projection onto convex sets (BPOCS), a novel de-blocking algorithm is proposed. A new smoothness constraint set (SCS) is used to remove the unnecessary high frequencies. In addition, an adaptive quantization constraint set (AQCS) is employed to suppress error in the smoothing process. The proposed size and position of new SCS are different from traditional ones. Extensive experimental results are provided to demonstrate that the proposed method can achieve better image quality with fewer iterations.

We discuss a new design methodology of polynomial neural networks (PNN) in the framework of genetic algorithm (GA). The PNN is based on the ideas of group method of data handling (GMDH). Each node in the network is very flexible and can carry out polynomial type mapping between input and output variables. But the performances of PNN depend strongly on the number of input variables available to the model, the number of input variables, and the type (order) of the polynomials to each node. In this paper, GA is implemented to better use the optimal inputs and the order of polynomial in each node of PNN. The appropriate inputs and order are evolved accordingly and are tuned gradually throughout the GA iterations. We employ a binary coding for encoding key factors of the PNN into the chromosomes. The chromosomes are made of three sub-chromosomes which represent the order, number of inputs, and input candidates for modeling. To construct model by using significant approximation and generalization, we introduce the fitness function with a weighting factor. Comparisons with other modeling methods and conventional PNN show that the proposed design method offers encouraging advantages and better performance.

Spatial despreading weight based on minimum mean square error (MMSE) criterion is derived for orthogonal space-time spreading transmit diversity (OSTSTD) in a fast fading channel, taking into account the inter-antenna interference (IAI) and the inter-code interference (ICI) caused by orthogonality distortion of time-domain spreading codes. Average bit error rate (BER) performance is theoretically analyzed and confirmed by computer simulation to show that the diversity gain can be obtained even in a fast fading.

A multi-stage approach -- which is fast, robust and easy to train -- for a face-detection system is proposed. Motivated by the work of Viola and Jones [1], this approach uses a cascade of classifiers to yield a coarse-to-fine strategy to reduce significantly detection time while maintaining a high detection rate. However, it is distinguished from previous work by two features. First, a new stage has been added to detect face candidate regions more quickly by using a larger window size and larger moving step size. Second, support vector machine (SVM) classifiers are used instead of AdaBoost classifiers in the last stage, and Haar wavelet features selected by the previous stage are reused for the SVM classifiers robustly and efficiently. By combining AdaBoost and SVM classifiers, the final system can achieve both fast and robust detection because most non-face patterns are rejected quickly in earlier layers, while only a small number of promising face patterns are classified robustly in later layers. The proposed multi-stage-based system has been shown to run faster than the original AdaBoost-based system while maintaining comparable accuracy.

We propose a method of face identification under various illumination conditions. Because we use image based method for identification, the accurate position of the face is required. First, face features are detected, and the face region is determined using the features. Then, by registering the face region to the average face, the horizontal position of the face is adjusted. Finally, the size of the face region is adjusted based on the distance of two eyes determined from all input frames. If the sizes of images for all faces are normalized into one size, the face length feature is lost in the normalized face image. The face is classified into three categories according to the face length, and the subspace is generated in each category so that the face length feature is preserved. We demonstrate the effectiveness of the proposed method by experiments.

This paper presents a view independent video-based face recognition method using posterior probability in Kernel Fisher Discriminant (KFD) space. In practical environment, the view of faces changes dynamically. Robustness to view changes is required for video-based face recognition in practical environment. Since the view changes induce large non-linear variation, kernel-based methods are appropriate. We use KFD analysis to cope with non-linear variation. To classify image sequence, the posterior probability in KFD space is used. KFD analysis assumes that the distribution of each class in high dimensional space is Gaussian. This makes the computation of posterior probability in KFD space easy. The combination of KFD space and posterior probability of image sequence is the main contribution of the proposed method. The performance is evaluated by using two face databases. Effectiveness of the proposed method is shown by the comparison with the other feature spaces and classification methods.

A second-order CMOS continuous-time bandpass filter with a tuneable 4-12 MHz center frequency (fc) is presented. The Design has been done by using a new second-order block which is based on Gm-C method. This Gm-C filter achieves a dynamic range of 30 dB for 1% IM3, and Q equal to 58 at 12 MHz, while dissipating only 10.5 mW from 3.3 V power supply in 0.35 µm CMOS process. The on-chip indirect automatic tuning circuit uses a phase-locked loop which sets filter center frequency to an external reference clock.

In this paper, we proposed a new Two-Dimensional Linear Discriminant Analysis (2DLDA) method, based on Two-Dimensional Principle Component Analysis (2DPCA) concept. In particular, 2D face image matrices do not need to be previously transformed into a vector. In this way, the spatial information can be preserved. Moreover, the 2DLDA also allows avoiding the Small Sample Size (SSS) problem, thus overcoming the traditional LDA. We combine 2DPCA and our proposed 2DLDA on the Two-Dimensional Linear Discriminant Analysis of principle component vectors framework. Our framework consists of two steps: first we project an input face image into the family of projected vectors via 2DPCA-based technique, second we project from these space into the classification space via 2DLDA-based technique. This does not only allows further reducing of the dimension of feature matrix but also improving the classification accuracy. Experimental results on ORL and Yale face database showed an improvement of 2DPCA-based technique over the conventional PCA technique.