Based on the theoretical analysis of literature, saturation in measured signal of active noise control (ANC) systems will degrade the convergence speed. However, the experiments show that the saturated input signal can speed up the convergence of the narrow-band ANC systems. This paper intends to remodel the saturation effects for feedforward and feedback ANC systems. Combining the action of analog-to-digital converters (ADC), the mathematical expression and block diagrams are proposed to model the saturation effects in the practical ANC systems. The derivation and simulation results show that since the saturation is able to amplify the principle component of signal, the convergence would be speeded up.

Petri net is a powerful modeling tool for concurrent systems. Liveness, which is a problem to verify there exists no local deadlock, is one of the most important properties of Petri net to analyze. Computational complexity of liveness of a general Petri net is deterministic exponential space. Liveness is studied for subclasses of Petri nets to obtain necessary and sufficient conditions that need less computational cost. These are mainly done using a subset of places called siphons. CS-property, which denotes that every siphon has token(s) in every reachable marking, in one of key properties in liveness analysis. On the other hand, normal Petri net is a subclass of Petri net whose reachability set can be effectively calculated. This paper studies computational complexity of liveness problem of normal Petri nets. First, it is shown that liveness of a normal Petri net is equivalent to cs-property. Then we show this problem is co-NP complete by deriving a nondeterministic algorithm for non-liveness which is similar to the algorithm for liveness suggested by Howell et al. Lastly, we study structural feature of bounded Petri net where liveness and cs-property are equivalent. From this consideration, liveness problem of bounded normal Petri net is shown to be deterministic polynomial time complexity.

The GNSS receivers suffer from the multipath interference which is highly correlated with the line of sight (LoS) signal. Such interference results in tracking and ranging errors. In this paper, we propose a novel algorithm that can estimate the direction of arrival (DoA) of the LoS signal in the presence of highly correlated multipath interference. The proposed algorithm combines the matching pursuits algorithm for multipath estimation and the minimum norm algorithm for DoA estimation. An efficient combination of two algorithms yields reliable estimates of the DoA of LoS signal as demonstrated by computer simulations.

A Generalized Symbol-rate-increased (GSRI) Pragmatic Adaptive Trellis Coded Modulation (ATCM) is applied to a Multi-carrier CDMA (MC-CDMA) system with bi-orthogonal keying is analyzed. The MC-CDMA considered in this paper is that the input sequence of a bi-orthogonal modulator has code selection bit sequence and sign bit sequence. In, an efficient error correction code using Reed-Solomon (RS) code for the code selection bit sequence has been proposed. However, since BPSK is employed for the sign bit modulation, no error correction code is applied to it. In order to realize a high speed wireless system, a multi-level modulation scheme (e.g. MPSK, MQAM, etc.) is desired. In this paper, we investigate the performance of the MC-CDMA with bi-orthogonal keying employing GSRI ATCM. GSRI TC-MPSK can arbitrarily set the bandwidth expansion ratio keeping higher coding gain than the conventional pragmatic TCM scheme. By changing the modulation scheme and the bandwidth expansion ratio (coding rate), this scheme can optimize the performance according to the channel conditions. The performance evaluations by simulations on an AWGN channel and multi-path fading channels are presented. It is shown that the proposed scheme has remarkable throughput performance than that of the conventional scheme.

This paper considers the problem of target location estimation in heterogeneous wireless sensor networks and proposes a novel algorithm using a factor graph to fuse the heterogeneous measured data. In the proposed algorithm, we map the problem of target location estimation to a factor graph framework and then use the sum-product algorithm to fuse the heterogeneous measured data so that heterogeneous sensors can collaborate to improve the accuracy of target location estimation. Simulation results indicate that the proposed algorithm provides high location estimation accuracy.

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.

The minimum initial marking problem of Petri nets (MIM) is defined as follows: "Given a Petri net and a firing count vector X, find an initial marking M0, with the minimum total token number, for which there is a sequence δ of transitions such that each transition t appears exactly X(t) times in δ, the first transition is enabled at M0 and the rest can be fired one by one subsequently." In a production system like factory automation, economical distribution of initial resources, from which a schedule of job-processings is executable, can be formulated as MIM. AAD is known to produce best solutions among existing algorithms. Although solutions by AMIM+ is worse than those by AAD, it is known that AMIM+ is very fast. This paper proposes new heuristic algorithms AADO and AMDLO, improved versions of existing algorithms AAD and AMIM+, respectively. Sharpness of solutions or short CPU time is the main target of AADO or AMDLO, respectively. It is shown, based on computing experiment, that the average total number of tokens in initial markings by AADO is about 5.15% less than that by AAD, and the average CPU time by AADO is about 17.3% of that by AAD. AMDLO produces solutions that are slightly worse than those by AAD, while they are about 10.4% better than those by AMIM+. Although CPU time of AMDLO is about 180 times that of AMIM+, it is still fast: average CPU time of AMDLO is about 2.33% of that of AAD. Generally it is observed that solutions get worse as the sizes of input instances increase, and this is the case with AAD and AMIM+. This undesirable tendency is greatly improved in AADO and AMDLO.

Hybrid automatic repeat request (HARQ) is employed for the Evolved Universal Terrestrial Radio Access (E-UTRA) downlink. The ACK/NACK signals from each user equipment (UE) are multiplexed by code division multiple access (CDMA) and transmitted via a physical uplink control channel (PUCCH). The ACK/NACK signals are code spread by the cyclic shift (CS) sequences made from zero auto-correlation (ZAC) sequences; however, the orthogonality of these sequences is not guaranteed depending on the propagation channels; moreover, the amount of inter-code interference (ICI) depends on the delay spread of the channel and the transmitting timing control error of each UE. In the conventional PUCCH structure, ICI between two ACK signals does not degrade their detection performance, whereas ICI between an ACK signal and a NACK signal degrades the detection performance. This causes a serious gap between the detection performances of ACK and NACK signals, because generally in a PUCCH, there are more ACK signals than NACK signals. In this paper, we propose a novel phase rotation scheme on the constellations of ACK/NACK signals that can resolve this issue, and the simulation evaluation results confirm the benefits of the proposed phase rotation scheme.

The joint source-channel coding problem is considered. The joint source-channel coding theorem reveals the existence of a code for the pair of the source and the channel under the condition that the error probability is smaller than or equal to ε asymptotically. The separation theorem guarantees that we can achieve the optimal coding performance by using the two-stage coding. In the case that ε = 0, Han showed the joint source-channel coding theorem and the separation theorem for general sources and channels. Furthermore the ε-coding theorem (0 ≤ ε <1) in the similar setting was studied. However, the separation theorem was not revealed since it is difficult in general. So we consider the separation theorem in this setting.

In this letter, power allocation methods are devised for Amplify-and-Forward (AF) opportunistic relaying systems aiming at minimizing the outage probability. First, we extend the result on outage probability in and develop an approximate expression to simplify the power allocation problem. A corresponding optimization problem is constructed and proved to be convex. Then an iterative numerical method is proposed to find the optimal power allocation factor. We also propose a near-optimal method which can directly calculate the power allocation factor to reduce computational complexity. Numerical results show that the proposed methods have a similar performance with the ideal one, and outperform equal power allocation significantly with little overhead.

We present an attractive approach for OFDM transmission using an adaptive pre-FFT equalizer, which can select ICI reduction mode according to channel condition, and a degenerated-inverse-matrix-based channel estimator (DIME), which uses a cyclic sinc-function matrix uniquely determined by transmitted subcarriers. In addition to simulation results, the proposed system with an adaptive pre-FFT equalizer and DIME has been laboratory tested by using a software defined radio (SDR)-based test bed. The simulation and experimental results demonstrated that the system at a rate of more than 100 Mbps can provide a bit error rate of less than 10-3 for a fast multi-path fading channel that has a moving velocity of more than 200 km/h with a delay spread of 1.9 µs (a maximum delay path of 7.3 µs) in the 5-GHz band.

Multiple-input-multiple-output (MIMO) wireless systems can not always have full spatial multiplexing gain due to the channel correlation problem caused by various factors such as the coupled antenna elements, and the key-hole effect of the propagation environment. In this paper, we proposed a channel reconfiguration technique to combat the rank deficiency problem of the involved MIMO wireless channels that can not afford high-order multiplexing gains. In the proposed approach, each mobile station can simultaneously receive several independent data streams from multiple base stations through a set of MMSE-based receive beamformers to suppress the multiple access interferences. Making use of the receive beamforming, which virtually produce the effect of a single antenna at each receive mobile, makes the transmit base station possible to reconfigure the MIMO downlink channel and then pre-cancel the co-channel interferences. The proposed signal processing mechanism that iteratively optimized the MMSE receive weights and the transmit precoders, which brings the reconfigured MIMO system about the high data throughput seen only with indoor MIMO systems having rich wireless channels. It is shown that as compared to the conventional MIMO system, the M4 system can achieve a significantly higher capacity which is proportional to the number of the linked base stations.

We carried out degradation analysis of a blue phosphorescent organic light emitting diode by both impedance spectroscopy and transient electroluminescence (EL) spectroscopy. The number of semicircles observed in the Cole-Cole plot of the modulus became three to two after the device was operated for 567 hours. Considering the effective layer thickness of the initial and degraded devices did not change by degradation and combining the analysis of the Bode-plot of the imaginary part of the modulus, the relaxation times of emission layer and hole-blocking with electron transport layers changed to nearly the same value by the increase of the resistance of emission layer. Decay time of transient EL of the initial device was coincident with that of the degraded one. These phenomena suggest that no phosphorescence quenching sites are generated in the degraded device, but the number of the emission sites decrease by degradation.

In PKC 2004, Choi et al. proposed an ID-based authenticated group key agreement (AGKA) protocol using bilinear pairings. Unfortunately, their protocol suffered from an impersonation attack and an insider colluding attack. In 2008, Choi et al. presented an improvement to resist insider attacks. In their modified protocol, they used an ID-based signature scheme on transcripts for binding them in a session to prevent replay of transcripts. In particular, they smartly used the batch verification technique to reduce the computational cost. In this paper, we first show that Choi et al.'s modified AGKA protocol still suffers from an insider colluding attack. Then, we prove that the batch verification of the adopted ID-based signature scheme in their modified protocol suffers from a forgery attack.

In this paper, an image restoration method using the Wiener filter is proposed. In order to bring the theory of the Wiener filter consistent with images that have spatially varying statistics, the proposed method adopts the locally adaptive Wiener filter (AWF) based on the universal Gaussian mixture distribution model (UNI-GMM) previously proposed for denoising. Applying the UNI-GMM-AWF for deconvolution problem, the proposed method employs the stationary Wiener filter (SWF) as a pre-filter. The SWF in the discrete cosine transform domain shrinks the blur point spread function and facilitates the modeling and filtering at the proceeding AWF. The SWF and UNI-GMM are learned using a generic training image set and the proposed method is tuned toward the image set. Simulation results are presented to demonstrate the effectiveness of the proposed method.

The RFID tag system has received attention as an identification source. Each RFID tag is attached to some object. With the unique ID of the RFID tag, a user identifies the object provided with the RFID tag, and derives appropriate information about the object. One of important applications of the RFID technology is the position estimation of RFID tags. It can be very useful to acquire the location information concerning the RFID tags. It can be applied to navigation systems and positional detection systems for robots etc. In this paper, we propose a new position estimation method of RFID tags by using a probabilistic approach. In this method, mobile objects (person and robot, etc.) with RFID readers estimate the positions of RFID tags with multiple communication ranges. We show the effectiveness of the proposed method by computer simulations.

This paper describes the application techniques of the latency insertion method (LIM) to CMOS circuit simulations. Though the existing LIM algorithm to CMOS circuit performs fast transient analysis, CMOS circuits are not modeled accurately. As a result, they do not provide accurate simulations. We propose a more accurate LIM scheme for the CMOS inverter circuit by adopting a more accurate model of the CMOS inverter characteristics. Moreover, we present the way to expand the LIM algorithm to general CMOS circuit simulations. In order to apply LIM to the general CMOS circuits which consist of CMOS NAND and NOR, we derive the updating formulas of the explicit form of the LIM algorithm. By using the explicit form of the LIM scheme, it becomes easy to take in the characteristics of CMOS NAND and NOR into the LIM simulations. As a result, it is confirmed that our techniques are useful and efficient for the simulations of CMOS circuits.

Boundary-based corner detection has been widely applied in spline curve fitting, automated optical inspection, image segmentation, object recognition, etc. In order to obtain good results, users usually need to adjust the length of region of support to resist zigzags due to quantization and random noise on digital boundaries. To automatically determine the length of region of support for corner detection, Teh-Chin and Guru-Dinesh presented adaptive approaches based on some local properties of boundary points. However, these local-property based approaches are sensitive to noise. In this paper, we propose a new approach to find the optimum length of region of support for corner detection based on a statistic discriminant criterion. Since our approach is based on the global perspective of all boundary points, rather than the local properties of some points, the experiments show that the determined length of region of support increases as the noise intensity strengthens. In addition, the detected corners based on the optimum length of region of support are consistent with human experts' judgment, even for noisy boundaries.

We propose a learning strategy for acceleration in learning speed of genetic programming (GP), named hierarchical structure GP (HSGP). The HSGP exploits multiple learning nodes (LNs) which are connected in a hierarchical structure, e.g., a binary tree. Each LN runs conventional evolutionary process to evolve its own population, and sends the evolved population into the connected higher-level LN. The lower-level LN evolves the population with a smaller subset of training data. The higher-level LN then integrates the evolved population from the connected lower-level LNs together, and evolves the integrated population further by using a larger subset of training data. In HSGP, evolutionary processes are sequentially executed from the bottom-level LNs to the top-level LN which evolves with the entire training data. In the experiments, we adopt conventional GPs and the HSGPs to evolve image recognition programs for given training images. The results show that the use of hierarchical structure learning can significantly improve learning speed of GPs. To achieve the same performance, the HSGPs need only 30-40% of the computation cost needed by conventional GPs.

In conjunction with a first-order Taylor series approximation of the spatial scanning vector, this letter presents an iterative multiple signal classification (MUSIC) direction-of-arrival (DOA) estimation for code-division multiple access signals. This approach leads to a simple one-dimensional optimization problem to find each iterative optimal search grid. It can not only accurately estimate DOA, but also speed up the estimating process. Computer results demonstrate the effectiveness of the proposed algorithm.