This paper focuses on fusion estimation algorithms weighted by matrices and scalars, and relationship between them is considered. We present new algorithms that address the computation of matrix weights arising from multidimensional estimation problems. The first algorithm is based on the Cholesky factorization of a cross-covariance block-matrix. This algorithm is equivalent to the standard composite fusion estimation algorithm however it is low-complexity. The second fusion algorithm is based on an approximation scheme which uses special steady-state approximation for local cross-covariances. Such approximation is useful for computing matrix weights in real-time. Subsequent analysis of the proposed fusion algorithms is presented, in which examples demonstrate the low-computational complexity of the new fusion estimation algorithms.

To solve the problem of distributed multisensor fusion, the optimal linear methods can be used in Gaussian noise models. In practice, channel noise distributions are usually non-Gaussian, possibly heavy-tailed, making linear methods fail. By combining a classical tool of optimal linear fusion and a robust statistical method, the two-stage MAD robust fusion (MADRF) algorithm is proposed. It effectively performs both in symmetrically and asymmetrically contaminated Gaussian channel noise with contamination parameters varying over a wide range.

We analyze the carrier dynamics in MOSFETs under low-voltage operation. For this purpose the displacement (charging/discharging) current, induced during switching operations is studied experimentally and theoretically for a 90 nm CMOS technology. It is found that the experimental transient characteristics can only be well reproduced in the circuit simulation of low voltage applications by considering the carrier-transit delay in the compact MOSFET model. Long carrier transit delay under the low voltage switching-on operation results in long duration of the displacement current flow. On the other hand, the switching-off characteristics are independent of the bias condition.

A novel bimodal method for face recognition under low-level lighting conditions is proposed. It fuses an enhanced gray level image and an illumination-invariant geometric image at the feature-level. To further improve the recognition performance under large variations in attributions such as poses and expressions, discriminant features are extracted from source images using the wavelet transform-based method. Features are adaptively fused to reconstruct the final face sample. Then FLD is used to generate a supervised discriminant space for the classification task. Experiments show that the bimodal method outperforms conventional methods under complex conditions.

We have previously proposed a diffusion-type flow control mechanism as a solution for severely time-sensitive flow control required for high-speed networks. In this mechanism, each node in a network manages its local traffic flow using the basis of only the local information directly available to it, by using predetermined rules. In addition, the implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies show that our flow control mechanism with certain parameter settings works well in high-speed networks. However, to apply this mechanism to actual networks, it is necessary to clarify how to design a parameter in our control mechanism. In this paper, we investigate the range of the parameter and derive its optimal value enabling the diffusion-type flow control to work effectively.

In on-line signature verification, complexity of signature shape can influence the value of the optimal threshold for individual signatures. Writer-dependent threshold selection has been proposed but it requires forgery data. It is not easy to collect such forgery data in practical applications. Therefore, some threshold equalization method using only genuine data is needed. In this letter, we propose three different threshold equalization methods based on the complexity of signature. Their effectiveness is confirmed in experiments using a multi-matcher DWT on-line signature verification system.

To design secure blockciphers, estimating immunity against differential attack and linear attack is essential. Recently, Diffusion Switching Mechanism (DSM) is proposed as a design framework to enhance the immunity of Feistel structure against differential attack and linear attack. In this paper, we give novel results on the effect of DSM on three generalized Feistel structures, i.e. Type-I, Type-II and Nyberg's structures. We first show a method for roughly estimating lower bounds of a number of active S-boxes in Type-I and Type-II structures using DSM. Then we propose an improved search algorithm to find lower bounds for generalized structures efficiently. Experimental results obtained by the improved algorithm show that DSM raises lower bounds for all of the structures, and also show that Nyberg's structure has the slowest diffusion effect among them when SP-type F-functions are used.

AlN/GaN Metal Insulator Semiconductor Field Effect Transistors (MISFETs) were designed, simulated and fabricated. DC, S-parameter and power measurements were also performed. Drift-diffusion simulations using DESSIS compared AlN/GaN MISFETs and Al32Ga68N/GaN Heterostructure FETs (HFETs) with the same geometries. The simulation results show the advantages of AlN/GaN MISFETs in terms of higher saturation current, lower gate leakage and higher transconductance than AlGaN/GaN HFETs. First results from fabricated AlN/GaN devices with 1 µm gate length and 200 µm gate width showed a maximum drain current density of 380 mA/mm and a peak extrinsic transconductance of 85 mS/mm. S-parameter measurements showed that current-gain cutoff frequency (fT) and maximum oscillation frequency (fmax) were 5.85 GHz and 10.57 GHz, respectively. Power characteristics were measured at 2 GHz and showed output power density of 850 mW/mm with 23.8% PAE at VDS = 15 V. To the authors knowledge this is the first report of a systematic study of AlN/GaN MISFETs addressing their physical modeling and experimental high-frequency characteristics including the power performance.

A new adaptive model based on fuzzy integrals has been presented and used for combining three well-known methods, Eigenface, Fisherface and SOMface, for face classification. After training the competence estimation functions, the adaptive mechanism enables our system the filtering of unsure judgments of classifiers for a specific input. Comparison with classical and non-adaptive approaches proves the superiority of this model. Also we examined how these features contribute to the combined result and whether they can together establish a more robust feature.

In this paper, a routing protocol referred to as Directed Diffusion with Stepwise Interest Retransmission (DD/SIR) for wireless sensor networks is proposed to mitigate power consumption considering node mobility. In DD/SIR, a sink retransmits interest. The propagation areas of the interest are narrowed stepwisely. In addition, according to the number of hops between the sink and sensor nodes, the data transmission timing is controlled sequentially. By both theoretical analysis and computer simulation, we evaluate the performance of DD/SIR. We show that DD/SIR can mitigate control overhead and realize low power operation without degrading data reachability to the sink. Especially, at a small number of data sending nodes, DD/SIR is more effective than the conventional routing.

In this paper, proactive data filtering (PDF) algorithm is proposed for data aggregation (or data fusion) in wireless sensor networks. The objective of the algorithm is to further reduce the energy consumption when sensor nodes perform data aggregation. In many applications, the sensor field will be overwhelmed by unnecessary and redundant sensory information when the sink node disseminates a query throughout the sensor field. In order to reduce the energy consumption, our scheme employs intelligent decision logic in the sensor node which delays or deactivates the transmission of its response. A performance evaluation shows that data aggregation with the PDF significantly improves energy-efficiency.

This paper proposes a robust omnidirectional audio-visual (AV) talker localizer for AV applications. The proposed localizer consists of two innovations. One of them is robust omnidirectional audio and visual features. The direction of arrival (DOA) estimation using an equilateral triangular microphone array, and human position estimation using an omnidirectional video camera extract the AV features. The other is a dynamic fusion of the AV features. The validity criterion, called the audio- or visual-localization counter, validates each audio- or visual-feature. The reliability criterion, called the speech arriving evaluator, acts as a dynamic weight to eliminate any prior statistical properties from its fusion procedure. The proposed localizer can compatibly achieve talker localization in a speech activity and user localization in a non-speech activity under the identical fusion rule. Talker localization experiments were conducted in an actual room to evaluate the effectiveness of the proposed localizer. The results confirmed that the talker localization performance of the proposed AV localizer using the validity and reliability criteria is superior to that of conventional localizers.

The reduction of a structural pattern at specific gray levels or at the special condition of image data has mainly been discussed in digital halftone methods. This problem is more severe in some flat panel displays because their black levels typically are brighter than other displays blocks. The authors proposed an advanced confined error diffusion (ACED) algorithm which was a well-organized halftone algorithm for flat panel devices. In this paper, we extend the ACED algorithm to the multi-level systems, which are capable of displaying more than 2 levels. Our extension has two merits for the hardware implementation. First, it can be processed in real time using the look-up table based method. The second one is the flexibility of selecting the used gray level. This paper discusses the performance of the proposed algorithms with experimental results for natural test images.

We propose LPDD (Lifetime Prediction Directed Diffusion), a novel energy-aware routing protocol for sensor networks that aims at increasing network survivability without a significant increase in latency. The key concept behind the protocol is the adaptive selection of routes by predicting the battery lifetime of the minimum energy nodes along the routes.

As the amount of recorded TV content is increasing rapidly, people need active and interactive browsing methods. In this paper, we use both text information from closed captions and visual information from video frames to generate links to enable users to easily explore not only the original video content but also augmented information from the Web. This solution especially shows its superiority when the video content cannot be fully represented by closed captions. A prototype system was implemented and some experiments were carried out to prove its effectiveness and efficiency.

The article describes recent adaptive estimation algorithms over distributed networks. The algorithms rely on local collaborations and exploit the space-time structure of the data. Each node is allowed to communicate with its neighbors in order to exploit the spatial dimension, while it also evolves locally to account for the time dimension. Algorithms of the least-mean-squares and least-squares types are described. Both incremental and diffusion strategies are considered.

Contact resistance is caused by constriction resistance and film resistance through contact layers. It is well known that a surface film causes non-linear voltage and current characteristics. The origin of non-linearity is caused by tunneling electron through thin insulation barrier or jumping over the thick barrier (Shottky barrier) on the contact surface. In this paper, a new idea causing nonlinear property by only current constriction which flows through very small contact spot area, if there is no film layer, is proposed by the two dimensional contact model. The contact model, used in this paper, is a two dimensional type narrow path of contact area (short bridge) made by thin copper foil of 0.035 mm on a glass epoxy resin board. The contact part is made by scraping with an electric drill as a single bridge shape of 0.1 mm wide and 0.3 mm long on the centre of a board (100 mm100 mm). The 3rd harmonic distortion voltage was measured by using a Component Linearity Test Equipment (Type CLT1 made by Radiometer Electronics Company) which the system supplies a pure sine wave current of 10 kHz and detects a distortion voltage of 30 kHz by a narrow band pass filter circuit. The sensitivity of the Component Linearity Test Equipment (CLT1) is under a 10-9 volt. Four bridge samples were examined for the comparison of nonlinear distortion voltage. The distortion voltage of a sample (A) (0.1 mm wide, 0.3 mm long) is too larger than the one of the sample (B) (0.2 mm wide, 0.3 mm long) at the same applied voltage which resistance is not so different each other. It seems that current constriction to the spot (A) may heat up higher and cool down lower than (B). It would be also guessed that the power dissipation of 20 kHz cause temperature oscillation of 20 kHz, then it causes a component of contact resistance of 20 kHz, and therefore the product of 10 kHz current and 20 kHz resistance component cause 30 kHz component distortion voltage.

The completeness (i.e. confluent and terminating) property is an important concept when using a term rewriting system (TRS) as a computational model of functional programming languages. Knuth and Bendix have proposed a procedure known as the KB procedure for generating a complete TRS. A TRS cannot, however, directly handle higher-order functions that are widely used in functional programming languages. In this paper, we propose a higher-order KB procedure that extends the KB procedure to the framework of a simply-typed term rewriting system (STRS) as an extended TRS that can handle higher-order functions. We discuss the application of this higher-order KB procedure to a certification technique called inductionless induction used in program verification, and its application to fusion transformation, a typical kind of program transformation.

In this paper, we present a general object tracking method based on a newly proposed pixel-wise clustering algorithm. To track an object in a cluttered environment is a challenging issue because a target object may be in concave shape or have apertures (e.g. a hand or a comb). In those cases, it is difficult to separate the target from the background completely by simply modifying the shape of the search area. Our algorithm solves the problem by 1) describing the target object by a set of pixels; 2) using a K-means based algorithm to detect all target pixels. To realize stable and reliable detection of target pixels, we firstly use a 5D feature vector to describe both the color ("Y, U, V") and the position ("x, y") of each pixel uniformly. This enables the simultaneous adaptation to both the color and geometric features during tracking. Secondly, we use a variable ellipse model to describe the shape of the search area and to model the surrounding background. This guarantees the stable object tracking under various geometric transformations. The robust tracking is realized by classifying the pixels within the search area into "target" and "background" groups with a K-means clustering based algorithm that uses the "positive" and "negative" samples. We also propose a method that can detect the tracking failure and recover from it during tracking by making use of both the "positive" and "negative" samples. This feature makes our method become a more reliable tracking algorithm because it can discover the target once again when the target has become lost. Through the extensive experiments under various environments and conditions, the effectiveness and efficiency of the proposed algorithm is confirmed.

We have previously developed a concatenative speech synthesizer based on the plural speech unit selection and fusion method that can synthesize stable and human-like speech. In this method, plural speech units for each speech segment are selected using a cost function and fused by averaging pitch-cycle waveforms. This method has a large computational cost, but some platforms require a speech synthesis system that can work within limited hardware resources. In this paper, we propose an offline unit fusion method that reduces the computational cost. In the proposed method, speech units are fused in advance to make a pre-fused speech unit database. At synthesis time, a speech unit for each segment is selected from the pre-fused speech unit database and the speech waveform is synthesized by applying prosodic modification and concatenation without the computationally expensive unit fusion process. We compared several algorithms for constructing the pre-fused speech unit database. From the subjective and objective evaluations, the effectiveness of the proposed method is confirmed by the results that the quality of synthetic speech of the offline unit fusion method with 100 MB database is close to that of the online unit fusion method with 93 MB JP database and is slightly lower to that of the 390 MB US database, while the computational time is reduced by 80%. We also show that the frequency-weighted VQ-based method is effective for construction of the pre-fused speech unit database.