We propose a user-defined on-demand matching strategy, called O-matching, in which users can control the order of matching arguments of each operation symbol. In ordinary matching schemes it is not important to set the order of matching, however, in on-demand matching schemes, it is very important since an input term may be changed while doing the on-demand matching process. O-matching is suitable to combine with the E-strategy, which is a user-defined reduction strategy in which users can control the order of reducing arguments. We show a sufficient condition under which the E-strategy with O-matching is correct for head normal forms, that is, any reduced term is a head normal form.

The performance of ultra-wideband (UWB) multiple input multiple output (MIMO) receiver based on the RAKE maximal ratio combiner (MRC) followed by a zero forcing (ZF) detector is analytically examined. For a UWB MIMO system with NT transmit antennas, NR receive antennas, and L resolvable multipath components, the proposed MIMO detection scheme is shown to have the diversity order of LNR-NT+1 and its analytical error rate expression is presented in a log-normal fading channel. We also compare the analytical BERs with the simulated results.

Particle Swarm Optimization (PSO) is a search method which utilizes a set of agents that move through the search space to find the global minimum of an objective function. The trajectory of each particle is determined by a simple rule incorporating the current particle velocity and exploration histories of the particle and its neighbors. Since its introduction by Kennedy and Eberhart in 1995, PSO has attracted many researchers due to its search efficiency even for a high dimensional objective function with multiple local optima. The dynamics of PSO search has been investigated and numerous variants for improvements have been proposed. This paper reviews the progress of PSO research so far, and the recent achievements for application to large-scale optimization problems.

This study involves implementing an intelligent controller using the fuzzy control algorithm to minimize cold weld and splash in inverter AC spot welding. This study presents an experimental curve of a welding output current and the maximum value of the Instantaneous Heating Rate (IHRmax) using the contact diameter of an electrode as the parameter. It also presents the experimental curve of a welding output current and the slope (S) of the instantaneous dynamic resistance using the instantaneous contact area of an electrode as the parameter. To minimize cold weld and splash, this study proposes an intelligent controller that controls the optimum welding current in real time by estimating the contact diameter of an electrode and the contact area of the initial welding part.

To attain good performance in an acoustic echo cancellation system, it is important to have a variable step size (VSS) algorithm as part of an adaptive filter. In this paper, we are concerned with the development of a VSS algorithm for a recently proposed subband affine projection (SAP) adaptive filter. Two popular VSS algorithms in the literature are the methods of delayed coefficients (DC) and variable regularization (VR). However, the merits and demerits of them are mutually exclusive. We propose a VSS algorithm that is a hybrid of both methods and combines their advantages. An extensive study of the new algorithm in different scenarios like the presence double-talk (DT) during the transient phase of the adaptive filter, DT during steady state, and varying DT power is conducted and reasoning is given to support the observed behavior. The importance of the method of VR as part of a VSS algorithm is emphasized.

A single-carrier multiple-input multiple-output (MIMO) system with frequency-selective channels suffers from the inter-symbol interference (ISI) and the co-channel interference (CCI). To eliminate both type of interference, we propose in this letter a hybrid two-stage decision-feedback equalizer (HTS-DFE), which performs the frequency-domain equalization (FDE) in the first stage and the layered serial interference-cancellation (SIC) in the second stage. Since the decision-feedback (DF) or noise-prediction (NP) architecture can be employed in FDE or SIC, the proposed equalizer actually can have four variations that achieve the same mean square error (MSE) under the assumption of perfect feedback. Further, we combine HTS-DFE with the decoded decision-feedback (DDF) scheme to mitigate the error-propagation encountered in the practice. Simulation results confirm that the proposed HTS-DFE can outperform the existing equalizers significantly.

A reduced complexity quantization error correction method for lattice reduction aided (LRA) vector precoding is proposed. For LRA vector precoding,Babai's approximation procedure can generate quantization errors leading to performance loss. Instead of making a list to correct all possible errors as is done in the existing scheme, we propose a novel method in which only a subset of all possible errors are corrected. The size of the subset is determined by the probability distribution of the number of actual errors. Thus, the computation complexity of our correction procedure is reduced with little performance loss compared with the existing correction scheme.

Recently, it has become important to rapidly detect human subjects buried under collapsed houses, rubble and soil due to earthquakes and avalanches to reduce the casualties in a disaster. Such detection systems have already been developed as one kind of microwave displacement sensors that are based on phase difference generated by the motion of the subject's breast. Because almost all the systems consist of single transmitter and receiver pair, it is difficult to rapidly scan a wide area. In this paper, we propose a single-frequency multistatic radar system to detect breathing human subjects which exist in the area surrounded by the transmitting and receiving array. The vibrating targets can be localized by the MUSIC algorithm with the complex amplitude in the Doppler frequency. This algorithm is validated by the simulated signals synthesized with a rigorous solution of a dielectric spherical target model. We show experimental 3D localization results using a developed multistatic Doppler radar system around 250 MHz.

A data stream is a series of massive unbounded tuples continuously generated at a rapid rate. Continuous queries for data streams should be processed continuously, so that a strict time constraint is required. In most previous research studies, in order to guarantee this constraint, the evaluation order of join predicates in a continuous query is optimized using a greedy strategy. However, because a greedy strategy traces only the first promising plan, it often finds a suboptimal plan. To reduce the possibility of producing a suboptimal plan, in this paper, we propose an improved scheme, k-Extended Greedy Algorithm (k-EGA), that simultaneously examines a set of promising plans and reoptimize an execution plan adaptively. The number of promising plans is flexibly controlled by a user-defined range variable. The scheme verifies the performance of the current plan periodically. If the plan is no longer efficient, a newly optimized plan is generated. The performance of the proposed scheme is verified through various experiments to identify its various characteristics.

Synchronization poses a major challenge in ultra wideband (UWB) systems due to low signal duty cycles in UWB. This study develops an effective synchronization scheme for frame-differential IR-UWB receivers to improve the synchronization speed. The proposed parallel search mechanism reduces the search region of the symbol boundaries to only a single frame duration. Moreover, only one delay element is needed in each branch, since a shared looped delay-line (SLD) is also proposed to lower the implementation complexity of the parallel search mechanism. Simulations and performance analysis show that the proposed scheme achieves a lower mean square error and a higher probability of detection than other alternatives.

In this paper, we propose a new digital duplexing scheme, called synchronous digital duplexing (SDD), which can increase data efficiency and flexibility of resource by transmitting uplink signal and downlink signal simultaneously in wireless communication. In order to transmit uplink and downlink signals simultaneously, the proposed SDD obtains mutual information among subscriber stations (SSs) with a mutual ranging symbol. This information is used for selection of transmission time, decision on cyclic suffix (CS) insertion, determination of CS length, and re-establishment of FFT starting point.

Optical buffer memory for 10-Gb/s data signal is demonstrated experimentally using a polarization bistable vertical-cavity surface-emitting laser (VCSEL). The optical buffer memory is based on an optical AND gate function and the polarization bistability of the VCSEL. Fast AND gate operation responsive to 50-ps-width optical pulses is achieved experimentally by increasing the detuning frequency between an injection light into the VCSEL and a lasing light from the VCSEL. A specified bit is extracted from the 10-Gb/s data signal by the fast AND gate operation and is stored as the polarization state of the VCSEL by the polarization bistability. The corresponding numerical simulations are also performed using two-mode rate equations taking into account the detuning frequency. The simulation results confirm the fast AND gate operation by increasing the detuning frequency as well as the experimental results.

In this paper, we propose block matching and learning for color image classification. In our method, training images are partitioned into small blocks. Given a test image, it is also partitioned into small blocks, and mean-blocks corresponding to each test block are calculated with neighbor training blocks. Our method classifies a test image into the class that has the shortest total sum of distances between mean blocks and test ones. We also propose a learning method for reducing memory requirement. Experimental results show that our classification outperforms other classifiers such as support vector machine with bag of keypoints.

An antenna-permutation (AP) scheme is described for channel-vector quantization (CVQ) in zero-forcing beamforming (ZFBF) multiuser multiple-input and multiple-output orthogonal frequency-division multiplexing systems with multiple receive antennas. Different sets of multiple channel sub-matrices are selected for different subcarriers and then quantized to multiple quantization vectors for finite rate feedback. Based on the quantization vectors, ZFBF provides a single stream or multiple streams to users while increasing frequency selectivity. Simulation results demonstrate that AP-CVQ with four-bit quantization that incorporates with pre-whitening maximum likelihood detection for two stream reception achieved better average packet error rates than minimum mean square error receive beamforming for single stream reception when the frequency selectivity was not severe.

An equalizer initialization technique for least mean squares (LMS) algorithm, which can equalize frequency selective multiple input multiple output (MIMO) channels, is presented and analyzed. The proposed method conducts an initial convergence step for superior training prior to running the LMS algorithm. This approach raises the training performance while the complexity of the LMS algorithm, which is known as the simplest training algorithm, is almost the same. The proposed technique is analyzed for the initial convergence and simulated for a possible single carrier MIMO application in single carrier (SC) IEEE802.16-2004 standards. The obtained performance after coding approximates the performance of the recursive least squares (RLS) algorithm as it is presented for 33 and 55 MIMO for comparisons.

The fuzzy controller based on cycle-to-cycle control with output value adjustment factors (OAF) was developed for restoring gait of paralyzed subjects by using functional electrical stimulation (FES). Results of maximum knee flexion and extension controls with neurologically intact subjects suggested that the OAFs would be effective in reaching the target within small number of cycles and in reducing the error after reaching the target. Oscillating responses between cycles were also suppressed. The fuzzy controller was expected to be examined to optimize the OAFs with more subjects including paralyzed patients for clinical application.

Video summarization is defined as creating a video summary which includes only important scenes in the original video streams. In order to realize automatic video summarization, the significance of each scene needs to be determined. When targeted especially on broadcast sports videos, a play scene, which corresponds to a play, can be considered as a scene unit. The significance of every play scene can generally be determined based on the importance of the play in the game. Furthermore, the following two issues should be considered: 1) what is important depends on each user's preferences, and 2) the summaries should be tailored for media devices that each user has. Considering the above issues, this paper proposes a unified framework for user and device adaptation in summarizing broadcast sports videos. The proposed framework summarizes sports videos by selecting play scenes based on not only the importance of each play itself but also the users' preferences by using the metadata, which describes the semantic content of videos with keywords, and user profiles, which describe users' preference degrees for the keywords. The selected scenes are then presented in a proper way using various types of media such as video, image, or text according to device profiles which describe the device type. We experimentally verified the effectiveness of user adaptation by examining how the generated summaries are changed by different preference degrees and by comparing our results with/without using user profiles. The validity of device adaptation is also evaluated by conducting questionnaires using PCs and mobile phones as the media devices.

This article explains how to apply the deterministic annealing (DA) and simulated annealing (SA) methods to fuzzy entropy based fuzzy c-means clustering. By regularizing the fuzzy c-means method with fuzzy entropy, a membership function similar to the Fermi-Dirac distribution function, well known in statistical mechanics, is obtained, and, while optimizing its parameters by SA, the minimum of the Helmholtz free energy for fuzzy c-means clustering is searched by DA. Numerical experiments are performed and the obtained results indicate that this combinatorial algorithm of SA and DA can represent various cluster shapes and divide data more properly and stably than the standard single DA algorithm.

In this letter, a pilot-less sampling frequency offset estimation scheme is presented for ultra-wideband orthogonal frequency division multiplexing (UWB-OFDM) systems. This scheme is based on the fact that two consecutive symbols convey the same information in the UWB-OFDM system, thus removing the need of pilot symbols. The performance of mean square error has been evaluated through simulation to verify the usefulness of the proposed scheme.

A method that jointly estimates the carrier frequency offset (CFO), channel and symbol timing for orthogonal frequency division multiplexing (OFDM) is proposed in this letter. Based on the characteristic of cyclic training symbols in the frequency domain, the joint estimation is divided into three separate estimations. The CFO and equivalent channel impulse response (CIR) are first estimated by an iterative joint maximum likelihood estimation (JMLE), then the symbol timing offset (STO) is obtained by the assistance of equivalent CIR, finally the CIR is calculated based on the equivalent CIR after known STO and CFO. In our proposed method, the effect of imperfect CIR is considered in the CFO estimator. Moveover, a procedure, which eliminates the inverse operation of a covariance matrix at each iterative process, was adopted to reduce the complexity of our proposed method. Simulations show that the proposed method is capable of retaining the same bit error rate as joint CFO and CIR maximum likelihood estimation without symbol timing error.