Recently, for more efficient filtering of XML data, YFilter system has been suggested to exploit the prefix commonalities that exist among path expressions. Sharing the prefix commonality gives the benefit of improving filtering performance through the tremendous reduction in filtering machine size. However, exploiting the postfix commonality can also be useful for an XML filtering situation. For example, when a stream of XML messages does not have any defined schema, or users cannot remember the defined schema exactly, users often use the partial matching path queries which begins with the descendant axis ("//"), e.g., '//science/article/title', '//entertainment/article/title', and '//title'. If so, the registered XPath queries are most likely to have the postfix commonality, e.g., the sample queries share the partial path expressions 'article/title' and 'title'. Therefore, in this paper, we introduce a bottom-up filtering approach exploiting the postfix commonality against the top-down approach of YFilter exploiting the prefix commonality. Some experimental results show that our method has better filtering performance when registered XPath queries mainly consist of the partial matching path queries with the postfix commonality.

In this letter, a new estimation filtering is proposed when a delay between signal generation and signal estimation exists. The estimation filter is developed under a maximum likelihood criterion using only the finite observations on the delay interval. The proposed estimation filter is represented in both matrix form and iterative form. It is shown that the filtered estimate has good inherent properties such as time-invariance, unbiasedness and deadbeat. Via numerical simulations, the performance of the proposed estimation filtering is evaluated by the comparison with that of the existing fixed-lag smoothing, which shows that the proposed approach could be appropriate for fast estimation of signals that vary relatively quickly. Moreover, the on-line computational complexity of the proposed estimation filter is shown to be maintained at a lower level than the existing one.

This paper presents a closed form solution to a problem of constructing the best lower bound of a convex function under certain conditions. The function is assumed (I) bounded below by -ρ, and (II) differentiable and its derivative is Lipschitz continuous with Lipschitz constant L. To construct the lower bound, it is also assumed that we can use the values ρ and L together with the values of the function and its derivative at one specified point. By using the proposed lower bound, we derive a computationally efficient deep monotone approximation operator to the level set of the function. This operator realizes better approximation than subgradient projection which has been utilized, as a monotone approximation operator to level sets of differentiable convex functions as well as nonsmooth convex functions. Therefore, by using the proposed operator, we can improve many signal processing algorithms essentially based on the subgradient projection.

Space-time trellis coding systems employing orthogonal frequency division multiplexing technique over frequency-selective channels is considered, where fading gains vary within a frame interval. The channel time-evolution of each sub-carrier is modeled by an autoregressive process, while the receiver utilizing a recursive technique combining Kalman filtering with per-survivor processing is studied.

In this letter a new structure of multifunctional frequency filter using a universal voltage conveyor (UVC) is presented. The multifunctional circuit can realize a low-pass, high-pass and band-pass filter. All types of frequency filter can be realized as inverting or non-inverting. Advantages of the proposed structure are the independent control of the quality factor at the cut-off frequency and the low output impedance of output terminals. The computer simulations and measuring of particular frequency filters are depicted.

This paper proposes a closed form solution to L2-sensitivity minimization of second-order state-space digital filters subject to L2-scaling constraints. The proposed approach reduces the constrained optimization problem to an unconstrained optimization problem by appropriate variable transformation. Furthermore, restricting ourselves to the case of second-order state-space digital filters, we can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, L2-sensitivity is expressed in closed form, and its minimization subject to L2-scaling constraints is achieved without iterative calculations.

This paper presents a method for markerless human motion capture using a single camera. It uses tree-based filtering to efficiently propagate a probability distribution over poses of a 3D body model. The pose vectors and associated shapes are arranged in a tree, which is constructed by hierarchical pairwise clustering, in order to efficiently evaluate the likelihood in each frame. A new likelihood function based on silhouette matching is proposed that improves the pose estimation of thinner body parts, i.e. the limbs. The dynamic model takes self-occlusion into account by increasing the variance of occluded body-parts, thus allowing for recovery when the body part reappears. We present two applications of our method that work in real-time on a Cell Broadband EngineTM: a computer game and a virtual clothing application.

This paper presents a fuzzy partitioning method that adaptively divides a global key pool into multiple partitions by a fuzzy logic in the statistical filtering-based sensor networks. Compared to the original statistical filtering scheme, the proposed method is more resilient against node compromise.

We investigate a least squares (LS) based multi-step autoregressive (AR) prediction filter for delay compensation over MIMO channels. We describe the robustness of an adaptive MIMO-OFDM with that filter over mobile fading channels.

Using Bloom filters is one of the most popular and efficient lookup methods in P2P networks. A Bloom filter is a representation of data item indices, which achieves small memory requirement by allowing one-sided errors (false positive). In the lookup scheme besed on the Bloom filter, each peer disseminates a Bloom filter representing indices of the data items it owns in advance. Using the information of disseminated Bloom filters as a clue, each query can find a short path to its destination. In this paper, we propose an efficient extension of the Bloom filter, called a Deterministic Decay Bloom Filter (DDBF) and an index dissemination method based on it. While the index dissemination based on a standard Bloom filter suffers performance degradation by containing information of too many data items when its dissemination radius is large, the DDBF can circumvent such degradation by limiting information according to the distance between the filter holder and the items holders, i.e., a DDBF contains less information for faraway items and more information for nearby items. Interestingly, the construction of DDBFs requires no extra cost above that of standard filters. We also show by simulation that our method can achieve better lookup performance than existing ones.

A robust multichannel sound reproduction system that utilizes the relationship between the width of the actual control area and the control frequency of the control points is proposed. The reproduction accuracy of a conventional sound reproduction system is reduced by room environment variations when fixed inverse filter coefficients are used. This tendency becomes more significant when control points are arranged more closely. To resolve this problem, the frequency control band at every control point is switched to avoid degrading the reproduced sound in low frequencies, so the pass band range of the control points at both ears is only high-range. That of the other control points is the entire control range. Numerical simulation with real environmental data showed that improvement of the reproduction accuracy is about 6.1 dB on average, even with a temperature fluctuation of 5C as an environmental variation in the listening room.

This paper presents a very wideband active RC polyphase filter (ARCPF). We propose a unit section of the ARCPF, which is an ordinary RCPF followed by opamps with parallel RC feedback. In the proposed unit section, pole and zero can be assigned independently. By using the unit ARCPFs, a very wideband image rejection filter can be realized by cascading the sections, which can greatly reduce the element value spread. To realize this, CMOS inverter based fully differential OTA which can operate under low supply voltage is also presented. This paper describes a six-stage active RC polyphase filter with 1-100 MHz passband in 0.18 µm CMOS technology.

Speech dereverberation is one of the most difficult tasks in acoustic signal processing. Of the various problems involved in this task, this paper highlights "over-whitening," which flattens the characteristics of recovered speech. This distortion sometimes happens when inverse filters are directly calculated from microphone signals. This paper reviews two studies related to this problem. The first study shows the possibility of compensating for such over-whitening to achieve precise speech-dereverberation. The second study presents a new approach for approximating the original speech by removing the effect of late reflections from observed reverberant speech.

Spatial filtering is a useful method to suppress undesired reflection from unwanted scatters in Radar Cross Section (RCS) measurements. Actually, it is difficult to prepare an ideal field which satisfies the far-field criterion for RCS measurements of large targets. We applied the filtering method to a bistatic RCS measurement in a near field and investigated the validity of that method by varying the scanning angular span. Electromagnetic simulations show that predicted RCS profiles from near-field data with unwanted scatters closely matched far-field reference data of the test target. In conclusion, the results show that the method is effective for bistatic RCS measurements in practical field enviroments.

High-speed wireless communication systems have attracted much attention in recent years. To achieve a high-speed wireless communication system that utilizes an ultra-wide-frequency band, a broadband antenna is required. However, it is difficult to obtain an antenna that has uniform characteristics in a broad frequency band. Moreover, propagation characteristics are distorted in a multi-path environment. Thus, the communication quality tends to degrade due to the distortion in the frequency characteristics of the wideband communication system. This paper proposes a quasi-inverse filter (QIF) to improve the compensation effect for the transmitter antenna. Furthermore, we propose a method that employs the newly developed QIF that compensates for frequency characteristic distortion. We evaluate different configurations for the compensation system employing a pre-filter and post-filter in the wideband communication system. The effectiveness of the QIF in the case of severe distortion is verified by computer simulation. The proposed method is applied to a disc monopole antenna as a concrete example of a broadband antenna, and the compensation effect for the antenna is indicated.

A three-phase complex filter for a balanced three-phase analog signal processing is proposed. The proposed three-phase active-RC Tow-Thomas biquad complex filter can reduce total resistance by 10 percent, total capacitance by 25 percent, and power consumption by 22 percent compared to a conventional fully differential quadrature complex one.

We propose a new robust frequency domain acoustic echo cancellation filter that employs a normalized residual echo enhancement. By interpreting the conventional robust step-size control approaches as a statistical-model-based residual echo enhancement problem, the optimal step-size introduced in the most of conventional approaches is regarded as optimal only on the assumption that both the residual echo and the outlier in the error output signal are described by Gaussian distributions. However, the Gaussian-Gaussian mixture assumption does not always hold well, especially when both the residual echo and the outlier are speech signals (known as a double-talk situation). The proposed filtering scheme is based on the Gaussian-Laplacian mixture assumption for the signals normalized by the reference input signal amplitude. By comparing the performances of the proposed and conventional approaches through the simulations, we show that the Gaussian-Laplacian mixture assumption for the normalized signals can provide a better control scheme for the acoustic echo cancellation.

The Bloom Filter (BF), a space-and-time-efficient hash-coding method, is used as one of the fundamental modules in several network processing algorithms and applications such as route lookups, cache hits, packet classification, per-flow state management or network monitoring. BF is a simple space-efficient randomized data structure used to represent a data set in order to support membership queries. However, BF generates false positives, and cannot count the number of distinct elements. A counting Bloom Filter (CBF) can count the number of distinct elements, but CBF needs more space than BF. We propose an alternative data structure of CBF, and we called this structure an Adaptive Bloom Filter (ABF). Although ABF uses the same-sized bit-vector used in BF, the number of hash functions employed by ABF is dynamically changed to record the number of appearances of a each key element. Considering the hash collisions, the multiplicity of a each key element on ABF can be estimated from the number of hash functions used to decode the membership of the each key element. Although ABF can realize the same functionality as CBF, ABF requires the same memory size as BF. We describe the construction of ABF and IABF (Improved ABF), and provide a mathematical analysis and simulation using Zipf's distribution. Finally, we show that ABF can be used for an unpredictable data set such as real network traffic.

The multistage Wiener filter (MWF) outperforms the full rank Wiener filter in low sample support environments. However, the MWF adaptive process should be stopped at an optimum stage to get the best performance. There are two methods to stop the MWF adaptive process. One method is to calculate until the final full-stage, and the second method is to terminate at r-stage less than full-stage. The computational load is smaller in the latter method, however, a performance degradation is caused by an additional or subtractive stage calculation. Therefore, it is very important for the r-stage calculation to stop an adaptive process at the optimum stage. In this paper, we propose a simple method based on a cross-correlation coefficient to stop the MWF adaptive process. Because its coefficient is calculated by the MWF forward recursion, the optimum stage is determined automatically and additional calculations are avoided. The performance was evaluated by simulation examples, demonstrating the superiority of the proposed method.

The MIMO system can meet the growing demand for higher capacity in wireless communication fields. So far, the authors have reported that, based on channel measurements, uncoded performance of narrowband MIMO spatial multiplexing in indoor line-of-sight (LOS) environments generally outperforms that in non-LOS (NLOS) ones under the same transmit power condition. In space-frequency coded MIMO-OFDM spatial multiplexing, however, we cannot expect high space-frequency diversity gain in LOS environments because of high fading correlations and low frequency selectivity of channels so that the performance may degrade unlike uncoded cases. In this letter, we present the practical performance of coded MIMO-OFDM spatial multiplexing based on indoor channel measurements. The results show that an LOS environment tends to provide lower space-frequency diversity effect whereas the MIMO-OFDM spatial multiplexing performance is still better in the environment compared with an NLOS environment.