A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

The Ubiquitous sensor network (USN) node is required to operate for several months with limited system resources such as memory and power. The typical USN node is in the active state for less than 1% of its several month lifetime and waits in the inactive state for the remaining 99% of its lifetime. This paper suggests a power adjustment dual priority scheduler (PA-DPS) that offers low power consumption while meeting the USN requirements by estimating power consumption in the USN node. PA-DPS has been designed based on the event-driven approach and the dual-priority scheduling structure, which has been conventionally suggested in the real-time system field. From experimental results, PA-DPS reduced the inactive mode current up to 40% under the 1% duty cycle.

The use of frequency-domain equalization based on minimum mean square error criterion (called MMSE-FDE) can significantly improve the bit error rate (BER) performance of DS-CDMA signal transmission compared to the well-known coherent rake combining. However, in a DS-CDMA cellular system, as a mobile user moves away from a base station and approaches the cell edge, the received signal power gets weaker and the interference from other cells becomes stronger, thereby degrading the transmission performance. To improve the transmission performance of a user close to the cell edge, the well-known site diversity can be used in conjunction with FDE. In this paper, we consider DS-CDMA downlink site diversity with FDE. The MMSE site diversity combining weight is theoretically derived for joint FDE and antenna diversity reception and the downlink capacity is evaluated by computer simulation. It is shown that the larger downlink capacity can be achieved with FDE than with coherent rake combining. It is also shown that the DS-CDMA downlink capacity is almost the same as MC-CDMA downlink capacity.

Bandpass filters with broad bandwidth (up to 70%), very wide upper stopband (nearest spurious passband occurs up to five times of passband center frequency (f0)), good stopband rejection performance (better than -30-40 dB in the whole stopband region), and matching with the conventional low cost printed circuit board process with low dielectric constant substrates are proposed in this paper. The proposed filters are designed using parallel-coupled vertically installed planar stepped-impedance resonators (VIPSIRs), which adopt the inherent nature of very tight coupling of VIP coupled line and extremely high impedance of VIP line. The extremely tightly coupled line enables the proposed filters having very wide passband and the extremely high impedance of VIP line leads to extremely large low-to-high impedance ratio that pushes the nearest spurious passband up to 5f0. Both VIP coupled line and VIP high impedance line are analyzed and characterized by the design charts. The design procedures based on the design charts are verified by several experimental examples. The measured results agree very well with the simulated ones.

The power reduction of display devices has become an important issue for extending battery life and running time when they are used in digital multimedia broadcasting (DMB) mobile phones. DMB mobile phones generally use 16-bit data per pixel to reduce power consumption even though a liquid crystal display (LCD) graphic controller can support 16-, 18-, and 24-bit data per pixel. Also, the total transmission time of 16-bit data per pixel is only half that for 18- and 24-bit data per pixel. Decoded 24-bit image data in the frame memory of a DMB decoder are asymmetrically truncated to 16-bit image data. This results in a lack of smoothness such as blocking effects and/or pseudo edge artifacts. To solve these problems, the author proposes and implements a new asymmetric pixel data truncation error compensation algorithm using 1-bit least significant bit (LSB) data expansion with correlated color information for the purpose of ensuring smoothness. In the experimental results, the proposed algorithm is able to correct various artifacts.

Imperfect transmission of satellite imagery results in the loss of image lines. This paper proposes a novel error concealment technique using LSB-based watermarking. We generate block description information and insert it into the LSB bit plane of the image. Missing lines after transmission are restored by extracting this block description information. Simulation results show outstanding performance of the proposed technique.

In this letter, we propose a novel approach to speech enhancement, which incorporates a new criterion based on residual noise shaping. In the proposed approach, our goal is to make the residual noise perceptually comfortable instead of making it less audible. A predetermined `comfort noise' is provided as a target for the spectral shaping. Based on some assumptions, the resulting spectral gain function turns out to be a slight modification of the Wiener filter while requiring very low computational complexity. Subjective listening test shows that the proposed algorithm outperforms the conventional spectral enhancement technique based on soft decision and the noise suppression implemented in IS-893 Selectable Mode Vocoder.

In this paper, we propose a new scheme to represent three-dimensional (3-D) dynamic scenes using a hierarchical decomposition of depth maps. In the hierarchical decomposition, we split a depth map into four types of images: regular mesh, boundary, feature point and number-of-layer (NOL) images. A regular mesh image is obtained by down-sampling a depth map. A boundary image is generated by gathering pixels of the depth map on the region of edges. For generating feature point images, we select pixels of the depth map on the region of no edges according to their influence on the shape of a 3-D surface, and convert the selected pixels into images. A NOL image includes structural information to manage the other three images. In order to render a frame of 3-D dynamic scenes, we first generate an initial surface utilizing the information of regular mesh, boundary and NOL images. Then, we enhance the initial surface by adding the depth information of feature point images. With the proposed scheme, we can represent consecutive 3-D scenes successfully within the framework of a multi-layer structure. Furthermore, we can compress the data of 3-D dynamic scenes represented by a mesh structure by a 2-D video coder.

In this paper, we present a new fast Fourier transform (FFT) algorithm to reduce the table size of twiddle factors required in pipelined FFT processing. The table size is large enough to occupy significant area and power consumption in long-point FFT processing. The proposed algorithm can reduce the table size to half, compared to the radix-22 algorithm, while retaining the simple structure. To verify the proposed algorithm, a 2048-point pipelined FFT processor is designed using a 0.18 µm CMOS process. By combining the proposed algorithm and the radix-22 algorithm, the table size is reduced to 34% and 51% compared to the radix-2 and radix-22 algorithms, respectively. The FFT processor occupies 1.28 mm2 and achieves a signal-to-quantization-noise ratio (SQNR) of more than 50 dB.

In order to obtain better generalization performance in supervised learning, model parameters should be determined appropriately, i.e., they should be determined so that the generalization error is minimized. However, since the generalization error is inaccessible in practice, the model parameters are usually determined so that an estimator of the generalization error is minimized. The regularized subspace information criterion (RSIC) is such a generalization error estimator for model selection. RSIC includes an additional regularization parameter and it should be determined appropriately for better model selection. A meta-criterion for determining the regularization parameter has also been proposed and shown to be useful in practice. In this paper, we show that there are several drawbacks in the existing meta-criterion and give an alternative meta-criterion that can solve the problems. Through simulations, we show that the use of the new meta-criterion further improves the model selection performance.

This paper presents 3D keyframe animation watermarking using orientation interpolators. 3D keyframe animation consists of a number of transform nodes, including a geometrical node from the initial model and several interpolator nodes that represent object movement. Therefore, the proposed algorithm randomly selects transform nodes with orientation interpolator nodes, then resamples the quaternion components to maintain a uniform key time. Thereafter, watermark bits are embedded into quaternion components with large rotation angles. Experimental results verify the robustness of the proposed algorithm to geometrical and timeline attacks, along with the subjective and objective quality of its invisibility.

This paper presents an active quality of service (QoS) aware service composition protocol for mobile ad hoc networks (MANETs), with the goal of conserving resources subject to QoS requirements. A problem of QoS based service composition in MANETs is transformed into a problem of the service path discovery. We extend Dynamic Source Routing protocol to discover and compose elementary services across the network. Some message processing measures are taken to effectively reduce control overhead. Simulation results demonstrate the effectiveness of the proposed protocol.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear discrete-time systems under bounded-real transformations, where the transformations are given by arbitrary transfer functions with magnitude bounded by unity. Our main result reveals that the values of the second-order modes are decreased under any of the above-mentioned transformations. This result is the generalization of the theory of Mullis and Roberts, who proved that the second-order modes are invariant under any allpass transformation, i.e. any lossless bounded-real transformation. We derive our main result by describing the controllability/observability Gramians of transformed systems with the help of the discrete-time bounded-real lemma.

This work is concerned with the problem of robot localization using standard RFID tags as landmarks and an RFID reader as a landmark sensor. A main advantage of such an RFID-based localization system is the availability of landmark ID measurement, which trivially solves the data association problem. While the main drawback of an RFID system is its low spatial accuracy. The result in this paper is an improvement of the localization accuracy for a standard short-range RFID sensor. One of the main contributions is a proposal of a machine learning approach in which multiple classifiers are trained to distinguish RFID-signal features of each location. Another contribution is a design tool for tag arrangement by which the tag configuration needs not be manually designed by the user, but can be automatically recommended by the system. The effectiveness of the proposed technique is evaluated experimentally with a real mobile robot and an RFID system.

This paper introduces a texture analysis mechanism utilizing multiresolution technique to reduce false motion detection and hence thoroughly improve the interpolation results for high-quality deinterlacing. Conventional motion-adaptive deinterlacing algorithm selects from inter-field and intra-field interpolations according to motion. Accurate determination of motion information is essential for this purpose. Fine textures, having high local pixel variation, tend to cause false detection of motion. Based on hierarchical wavelet analysis, this algorithm provides much better perceptual visual quality and considerably higher PSNR than other motion adaptive deinterlacers as shown. In addition, a recursive 3-field motion detection algorithm is also proposed to achieve better performance than the traditional 2-field motion detection algorithm with little memory overhead.

This paper presents a mathematically simple method of maximum SINR (Signal to Interference plus Noise Ratio) design of broadband MIMO (Multiple Input Multiple Output) communication systems adopting TDL (Tapped Delay Line) structure for spatio-temporal processing in both transmitter and receiver sides. The weight vectors in both ends are determined alternately, optimizing one side by fixing the other, and this operation is repeated until the SINR converges. The performance of MIMO systems using the proposed approach is investigated through computer simulations, and it is demonstrated that, though it requires high computational cost, the TDL structure brings high ability to mitigate the influence of frequency selective fading, particularly when the duration of the delay profile is long. Moreover, experimental results show that the equable distribution of the resources (weights and delay units) to both arrays is better choice than the concentration of them to one side of the transmitter or receiver.

In this paper, we present a new method to enhance classification performance of a multiple classifier system by combining a boosting technique called AdaBoost.M2 and Kernel Discriminant Analysis (KDA). To reduce the dependency between classifier outputs and to speed up the learning, each classifier is trained in a different feature space, which is obtained by applying KDA to a small set of hard-to-classify training samples. The training of the system is conducted based on AdaBoost.M2, and the classifiers are implemented by Radial Basis Function networks. To perform KDA at every boosting round in a realistic time scale, a new kernel selection method based on the class separability measure is proposed. Furthermore, a new criterion of the training convergence is also proposed to acquire good classification performance with fewer boosting rounds. To evaluate the proposed method, several experiments are carried out using standard evaluation datasets. The experimental results demonstrate that the proposed method can select an optimal kernel parameter more efficiently than the conventional cross-validation method, and that the training of boosting classifiers is terminated with a fairly small number of rounds to attain good classification accuracy. For multi-class classification problems, the proposed method outperforms both Boosting Linear Discriminant Analysis (BLDA) and Radial-Basis Function Network (RBFN) with regard to the classification accuracy. On the other hand, the performance evaluation for 2-class problems shows that the advantage of the proposed BKDA against BLDA and RBFN depends on the datasets.

In this paper, we describe a new ultrasonic oscillosensor and its application in a biological information measurement system. This ultrasonic sensor has a cylindrical tank of 26 mm (diameter)20 mm (height) filled with water and an ultrasonic probe. It detects the vibration of the target object by obtaining echo signals reflected from the water surface. This sensor can noninvasively detect the vibration of a patient by placing it under a bed frame. We propose a recognition system for humans in bed. Using this sensor, we could determine whether or not a patient is in the bed. Moreover, we propose a heart rate monitoring system using this sensor. When our system was tested on four volunteers, we successfully detected a heart rate comparable to that in the case of using an electrocardiograph. Fuzzy logic plays a primary role in the recognition. Consequently, this system can noninvasively determine whether a patient is in the bed as well as their heart rate using a constraint-free and compact device.

The intent of this letter is to propose an efficient timestamp based password authentication scheme using smart cards. We show various types of forgery attacks against Shen et al.'s timestamp-based password authentication scheme and improve their scheme to ensure robust security for the remote authentication process, keeping all the advantages of their scheme. Our scheme successfully defends the attacks that could be launched against other related previous schemes.

This letter introduces a simple way of estimating the integer frequency offset (IFO) of OFDM-based digital video broadcasting (DVB) systems. By modifying the conventional maximum likelihood (ML) estimator to include the multi-stage estimation strategy, the IFO estimator is derived. Simulations indicate that the proposed IFO estimator works robustly when compared to ML estimator.