This paper deals with stability analysis of hybrid systems. Such systems are characterized by a combination of continuous dynamics and logic based switching between discrete modes. Lyapunov theory is a well known methodology for the stability analysis of linear and nonlinear systems in control system literature. Construction of Lyapunov functions for hybrid systems is generally a difficult task, but once these functions are defined, stabilization of the system is straight-forward. The sum of squares (SOS) decomposition and semidefinite programming has also provided an efficient methodology for analysis of nonlinear systems. The computational method used in this paper relies on the SOS decomposition of multivariate polynomials. By using SOS, we construct a (some) Lyapunov function(s) for the hybrid system. The reduction techniques provide numerical solution of large-scale instances; otherwise they will be practically unsolvable. The introduced method can be used for hybrid systems with linear or nonlinear vector fields. Some examples are given to demonstrate the capabilities of the proposed approach.

This research aims to develop automatic knowledge mining of causality from texts for supporting an automatic question answering system (QA) in answering 'why' question, which is among the most crucial forms of questions. The out come of this research will assist people in diagnosing problems, such as in plant diseases, health, industrial and etc. While the previous works have extracted causality knowledge within only one or two adjacent EDUs (Elementary Discourse Units), this research focuses to mine causality knowledge existing within multiple EDUs which takes multiple causes and multiple effects in to consideration, where the adjacency between cause and effect is unnecessary. There are two main problems: how to identify the interesting causality events from documents, and how to identify the boundaries of the causative unit and the effective unit in term of the multiple EDUs. In addition, there are at least three main problems involved in boundaries identification: the implicit boundary delimiter, the nonadjacent cause-consequence, and the effect surrounded by causes. This research proposes using verb-pair rules learnt by comparing the Naïve Bayes classifier (NB) and Support Vector Machine (SVM) to identify causality EDUs in Thai agricultural and health news domains. The boundary identification problems are solved by utilizing verb-pair rules, Centering Theory and cue phrase set. The reason for emphasizing on using verbs to extract causality is that they explicitly make, in a certain way, the consequent events of cause-effect, e.g. 'Aphids suck the sap from rice leaves. Then leaves will shrink. Later, they will become yellow and dry.'. The outcome of the proposed methodology shown that the verb-pair rules extracted from NB outperform those extracted from SVM when the corpus contains high occurence of each verb, while the results from SVM is better than NB when the corpus contains less occurence of each verb. The verb-pair rules extracted from NB for causality extraction has the highest precision (0.88) with the recall of 0.75 from the plant disease corpus whereas from SVM has the highest precision (0.89) with the recall of 0.76 from bird flu news. For boundary determination, our methodology can handle very well with approximate 96% accuracy. In addition, the extracted causality results from this research can be generalized as laws in the Inductive-Statistical theory of Hempel's explanation theory, which will be useful for QA and reasoning.

We show the equivalence between the conventional frame synchronization in single-carrier systems and integer part estimation of frequency offset in OFDM systems and propose an efficient synchronization scheme. The proposed scheme achieves both OFDM symbol/frame timing and frequency offset estimation with only one well-designed OFDM training symbol, while previous synchronization algorithms need two OFDM training symbols at least. Numerical analysis shows that the proposed frequency estimator nearly achieves the Cramér-Rao lower bound for the variance of the frequency offset estimate, despite the reduction in the training sequence length.

We propose feedback-limited NFSRs (nonlinear feedback shift registers) which can generate periodic sequences of period 2k-1, where k is the length of the register. We investigate some characteristics of such periodic sequences. It is also shown that the scale of such NFSRs can be reduced by the feedback limitation. Some simulation and experimental results are shown including comparison with LFSRs (linear feedback shift registers) for conventional M-sequences and Gold sequences.

This paper is to investigate the application of fuzzy c-means clustering to the direct identification of coherent synchronous generators in power systems. Because of the conceptual appropriateness and computational simplicity, this approach is essentially a fast and flexible method. At first, the coherency measures are derived from the time-domain responses of generators in order to reveal the relations between any pair of generators. And then they are used as initial element values of the membership matrix in the clustering procedures. An application of the proposed method to the Taiwan power (Taipower) system is demonstrated in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations, operating conditions, data sampling interval, and power system stabilizers are also investigated, as well. The results are compared with those obtained from the similarity relation method. And thus it is found that the presented approach needs less computation time and can directly initialize a clustering process for any number of clusters.

Many researchers have attempted to solve the combinatorial optimization problems, that are NP-hard or NP-complete problems, by using neural networks. Though the method used in a neural network has some advantages, the local minimum problem is not solved yet. It has been shown that the Inverse Function Delayed (ID) model, which is a neuron model with a negative resistance on its dynamics and can destabilize an intended region, can be used as the powerful tool to avoid the local minima. In our previous paper, we have shown that the ID network can separate local minimum states from global minimum states in case that the energy function of the embed problem is zero. It can achieve 100% success rate in the N-Queen problem with the certain parameter region. However, for a wider parameter region, the ID network cannot reach a global minimum state while all of local minimum states are unstable. In this paper, we show that the ID network falls into a particular permanent oscillating state in this situation. Several neurons in the network keep spiking in the particular permanent oscillating state, and hence the state transition never proceed for global minima. However, we can also clarify that the oscillating state is controlled by the parameter α which affects the negative resistance region and the hysteresis property of the ID model. In consequence, there is a parameter region where combinatorial optimization problems are solved at the 100% success rate.

This letter studies frequency-locked rotations in a phase-locked loop (PLL) circuit as FM demodulator. A rotation represents a desynchronized steady state in the PLL circuit and is regarded as another type of self-excited oscillations with natural rotation frequencies. The rotation frequency can be locked at driving frequencies of modulation signals. This letter shows response curves for harmonic amplitude of frequency-locked rotations. They have several different features from response curves of van der Pol oscillator.

In this paper, we shall describe about a basic theory based on the concept of set-valued operators, suitable for available operation of extremely complicated large-scale network systems. Fundamental conditions for availability of system behaviors of such network systems are clarified in a form of fixed point theorem for system of set-valued operators. Here, the proof of this theorem is accomplished by the concept of Hausdorff's ball measure of non-compactness.

This paper presents interference suppression using a subband adaptive array (SBAA) for uplink space-time block coding (STBC) code division multiple access (CDMA) under a frequency selective fading (FSF) channel. The proposed scheme utilizes CDMA with STBC and a receive array antenna with SBAA processing at the receiver. The received signal is converted into the frequency domain before despreading and adaptive processing is performed for each subband. A novel SBAA construction is introduced to process CDMA signals based on STBC. To improve the performance of the proposed scheme, we evaluate STBC-SBAA using spreading codes cyclic prefix (CP). Simulation results demonstrate an improved performance of the proposed system for single and multiuser environments compared to competing related techniques.

Service differentiation is one of the key issues in the current Internet. In this paper, we focus on a recent proposal for proportional loss rate differentiation which employs a single FIFO queue, an AQM algorithm for computing the packet drop probability, and a counter-based packet dropping routine for achieving the intended proportional loss rate differentiation among classes. It is first shown that, when the target dropping probability of a class is large, the counter-based packet dropping routine may yield a significant amount of error between the target and measured drop probabilities for the class, and subsequently, fails to maintain the loss rate ratios between classes as intended. To avoid this problem, a new compensatory packet dropping routine is developed in this paper. Then, a series of simulation experiments are conducted using the ns-2 simulator to assess the performances of the two dropping routines under various congestion conditions and quality spacings between classes. The simulation results show that, unlike the counter-based dropping routine, the proposed compensatory dropping routine is effective in keeping the loss rate ratios between classes closely on target regardless of the degree of congestion and quality spacing between classes, while the two dropping routines perform similarly in terms of throughput and queueing delay in the bottleneck link. In addition, such robustness of the proposed routine is achieved without any additional control parameter or computational effort compared to the counter-based routine.

The present paper introduces an integrated construction of binary sequences having a zero-correlation zone. The cross-correlation function and the side-lobe of the auto-correlation function of the proposed sequence set is zero for the phase shifts within the zero-correlation zone. The proposed method enables more flexible design of the binary zero-correlation zone sequence set with respect to its member size, length, and width of zero-correlation zone. Several previously reported sequence construction methods of binary zero-correlation zone sequence sets can be explained as special cases of the proposed method.

A comparison among the possible nonlinear photonic interactions for scalable nanometer networks and quantum gates as well as for coherence retention in solids is made theoretically, and then numerical plottings are given, on the basis of the dipole length estimated from our µ-PL (microphotoluminescence) spectra of GaAs/AlGaAs coupled quantum dots (QDs) having a pair of 0.3 meV splittings. Furthermore, prospective device concepts based on these nonlinear multipolar interactions are given.

This letter presents a simple maximum likelihood (ML) estimation method with one training symbol for the integer frequency offset (IFO) in orthogonal frequency division multiplexing (OFDM) systems. We show that the proposed method performs better than the conventional one through Monte Carlo simulations.

The major application of digital data hiding techniques is to deliver confidential data secretly via public but unreliable computer networks. Most of the existing data hiding schemes, however, exploit the raw data of cover images to perform secret communications. In this paper, a novel data hiding scheme was presented with the manipulation of images based on the compression of side-match vector quantization (SMVQ). This proposed scheme provided adaptive alternatives for modulating the quantized indices in the compressed domain so that a considerable quantity of secret data could be artfully embedded. As the experimental results demonstrated, the proposed scheme indeed provided a larger payload capacity without making noticeable distortions in comparison with schemes proposed in earlier works. Furthermore, this scheme also presented a satisfactory compression performance.

A Verilog-AMS model of a fractional-N frequency synthesizer is presented that is capable of predicting spurious tones as well as noise and jitter performance. The model is based on a voltage-domain behavioral simulation. Simulation efficiency is improved by merging the voltage controlled oscillator (VCO) and the frequency divider. Due to the benefits of Verilog-AMS, the ΔΣ modulator which is incorporated in the synthesizer is modeled in a fully digital way. This makes it accurate enough to evaluate how the performance of the frequency synthesizer is affected by cyclic behavior in the ΔΣ modulator. The spur-minimizing effect of an odd initial condition on the first accumulator of the ΔΣ modulator is verified. Sequence length control and its effect on the fractional-N frequency synthesizer are also discussed. The simulated results are in agreement with prior published data on fractional-N synthesizers and with new measurement results.

This paper presents a method to automatically acquire a given noun's telic and agentive roles from corpus data. These relations form part of the qualia structure assumed in the generative lexicon, where the telic role represents a typical purpose of the entity and the agentive role represents the origin of the entity. Our proposed method employs a supervised machine-learning technique which makes use of template-based contextual features derived from token instances of each noun. The output of our method is a ranked list of verbs for each noun, across the different qualia roles. We also propose a variant of Spearman's rank correlation to evaluate the correlation of two top-N ranked lists. Using this correlation method, we represent the ability of the proposed method to identify qualia structure relative to a conventional template-based method.

An energy management circuit is proposed for self-powered ubiquitous sensor modules using vibration-based energy. With the proposed circuit, the sensor modules work with low duty cycle operation. Moreover, a two-tank circuit as a part of the energy management circuit is utilized to solve the problem that the average power density of ambient energy always varies with time while the power consumption of the sensor modules is constant and larger than it. In addition, the long start-up time problem is also avoided with the timing control of the proposed energy management circuit. The CMOS implementation and silicon verification results of the proposed circuit are also presented. Its validity is further confirmed with a vibration-based energy generation. The sensor module is used to supervise the vibration of machines and transfer the vibration signal discontinuously. A piezoelectric element acts as the vibration-to-electricity converter to realize battery-free operation.

In a time-invariant wireless channel, the multipath that exceeds the cyclic prefix (CP) or the guard interval (GI) causes orthogonal frequency division multiplexing (OFDM) systems to hardly achieve high data rate transmission due to the inter-symbol interference (ISI) and the inter-carrier interference (ICI). In this paper the new canceller scheme, named as Double Window Cancellation and Combining (DWCC) is proposed. It includes the entire symbol interval, delayed by multipath as a signal processing window and intends to improve the performance by combining the double windows that can be formed by the pre- and post-ISI cancellation and reconstruction to the received OFDM symbol interfered by the multipath exceeding the guard interval. The proposed scheme has two algorithm structures of the DWCC-I and -II which are distinguished by the operational sequence (Symbol-wise or Group-wise) to the OFDM symbols of the received packet and by the selection of the processing window in the iterative decision feedback processing. Since the performance of the canceller is dependant on the equalization, particularly on the initial equalization, the proposed schemes operate with the time and frequency domain equalizer in the initial and the iterative symbol detection, respectively. For the verification of the proposed schemes, each scheme is evaluated in the turbo coded OFDM for low (QPSK) and high level modulation systems (16QAM, 64QAM), and compared with the conventional canceller with respect to the performance and computational complexity. As a result, the proposed schemes do not have an error floor even for 64QAM in a severe frequency selective channel.

Note taking is a fundamental activity for learning, and many software tools which enable students to take digitized notes have been proposed. Digitized notes are advantageous because they can be easily edited, rearranged, and shared. Although many note-taking tools have been proposed, there has been little research to examine the effect of note annotation and rearrangement with a digitized tool in terms of knowledge acquisition. Therefore, we have investigated the effect of note annotation and rearrangement on how well lecture content is remembered by learners. By annotation, we mean adding both handwritten and typed text, and rearrangement includes moving and deleting handwritten notes. We developed a simple note-taking application specialized for explanation, and evaluated it through a laboratory experiment with eight participants. The results show that note annotation and rearrangement significantly improved how well the participants remembered lecture content. Thus, the effect of annotation and rearrangement on remembrance was confirmed with respect to digitized notes.

This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix inequality (LMI) problem. If solutions of a specific system exist, the scheme finds more than one solutions at a time, and these fixed potential solutions and variable PID gains are ready for tracking performance optimization. The effectiveness of the proposed control scheme is demonstrated by the numerical example of a cart-pole system.