On the basis of the RF characteristics of p-type diamond field-effect transistors (FETs) with hydrogen surface termination, we establish an equivalent circuit (EQC) model. From comparisons of three cases we reveal that to represent the device performance in the EQC, the source, gate, and drain resistance should be considered but that the gate-source and gate-drain resistance can be ignored. The features of diamond FETs are (1) a plateau of the gate capacitance in a certain gate voltage range. (2) maximum fT and fMAX cut-off frequencies near the threshold gate voltage, and (3) a high fMAX/fT ratio 3.8. We discuss these features in terms of the energy barrier between the gate metal and the two-dimensional hole channel and drift region below the gate.

This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.

Prior studies on limited feedback (LFB) beamforming in multiple-antenna orthogonal frequency division multiplexing (OFDM) have resorted to Monte-Carlo simulations to evaluate the system performance. This letter proposes a novel analytical framework, based on which the averaged signal-to-noise ratio and the ergodic capacity performance of clustering-based LFB beamforming in multiple-antenna OFDM systems are studied. Simulations are also provided to verify the analysis.

Two novel low complexity dual-mode pulse generator designs suitable for FFs with triggering mode control are presented. The proposed designs successfully integrate XOR/OR (AND/XNOR) functions into a unified pass transistor logic (PTL) module to provide control on single- or double-edge operations. The designs use as few as 8 transistors each and ingeniously avoid the signal degradation problem inherent in most PTL circuits. As the only dual-mode designs so far, the proposed designs also outperform rival single-mode designs in both aspects of circuit complexity and power consumption.

H∞ optimal control is one of the most successful achievements in the post modern control theory. In the H∞ optimal control, we design a controller that minimizes the H∞ norm of a given system. Although the algorithms to solve the problem have already been reported, they focus on numerical systems (systems without any unknown parameters) and, can not be applied for parametric systems (systems with unknown parameters). Given a parametric system, this paper presents an algorithm to compute the optimal H∞ norm of the system achieved by an output feedback controller. The optimal H∞ norm is expressed as , where φ(k) denotes a root of a bivariate polynomial. A numerical example is given to show the effectiveness of the algorithm.

Our research goal is to facilitate the sharing of stories with digital photographs. Some map websites now collect stories associated with peoples' relationships to places. Users map collections of places and include their intangible emotional associations with each location along with photographs, videos, etc. Though this framework of mapping stories is important, it is not sufficiently expressive to communicate stories in a narrative fashion. For example, when the number of the mapped collections of places is particularly large, it is neither easy for viewers to interpret the map nor is it easy for the creator to express a story as a series of events in the real world. This is because each narrative, in the form of a sequence of textual narratives, a sequence of photographs, a movie, or audio is mapped to just one point. As a result, it is up to the viewer to decide which points on the map must be read, and in what order. The conventional framework is fairly suitable for mapping and expressing fragments or snapshots of a whole story and not for conveying the whole story as a narrative using the entire map as the setting. We therefore propose a new framework, Spatial Slideshow, for mapping personal photo collections and representing them as stories such as route guidances, sightseeing guidances, historical topics, fieldwork records, personal diaries, and so on. It is a fusion of personal photo mapping and photo storytelling. Each story is conveyed through a sequence of mapped photographs, presented as a synchronized animation of a map and an enhanced photo slideshow. The main technical novelty of this paper is a method for creating three-dimensional animations of photographs that induce the visual effect of motion from photo to photo. We believe that the proposed framework may have considerable significance in facilitating the grassroots development of spatial content driven by visual communication concerning real-world locations or events.

As THz wave has the advantages of enough resolution and penetration to materials, it has been examined to be used for the imaging system. The propagation distance of THz wave is limited to be short. That is also the advantage for application to the indoor wireless communication etc. For the achievement of the ultra-high frequency oscillator (and concurrently transmitter) device, the properties of small, electronic excitation, the antenna constructed and being on the wafer are important. For the purpose, the Negative differential resistance Dual channel transistor (NDR-DCT) proposed by AIST is utilized. In this paper, as an initial theoretical analysis, we simulated the oscillation frequency of this device at about 100 GHz-1THz within the Terahertz band on which the above applications was expected. The equivalent circuit model of NDR-DCT was shown based on the analogy with the resonant tunnelling diode (RTDs), and the antenna as the resonance circuit part was designed by the numerical analysis. The possibility of the THz oscillation of this device was confirmed. The slit reflector that we proposed can realize the slot antenna on the device effectively and is suitable for three terminal structure semiconductor. its manufacturing is relatively easy.

A bit-depth scalability is proposed in an adaptive way based on modified inter-layer predictions of the spatial scalability. A simple prediction for high dynamic range (HDR) sequences is implemented to reduce the redundancy of the residual signals between the base layer which contains low dynamic range (LDR) sequences and the enhancement layer which contains HDR sequences by using scaling and offset values.

Today, localization of nodes in Wireless Sensor Networks (WSNs) is a challenging problem. Especially, it is almost impossible to guarantee that one algorithm giving optimal results for one topology will give optimal results for any other random topology. In this study, we propose a centralized, range- and anchor-based, hybrid algorithm called RH+ that aims to combine the powerful features of two orthogonal techniques: Classical Multi-Dimensional Scaling (CMDS) and Particle Spring Optimization (PSO). As a result, we find that our hybrid approach gives a fast-converging solution which is resilient to range-errors and very robust to topology changes. Across all topologies we studied, the average estimation error is less than 0.5 m. when the average node density is 10 and only 2.5% of the nodes are beacons.

This paper presents a new method for reconstruction of trigonometric polynomials, a specific class of bandlimited signals, from a number of integrated values of input signals. It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise rms measurements of periodic signal (or power and energy) based on the presented signal reconstruction. Based on the value of the integral of the original input (analogue) signal, with a known frequency spectrum but unknown amplitudes and phases, a reconstruction of its basic parameters is done by the means of derived analytical and summarized expressions. Subsequent calculation of all relevant indicators related to the monitoring and processing of ac voltage and current signals is provided in this manner. Computer simulation demonstrating the precision of these algorithms. We investigate the errors related to the signal reconstruction, and provide an error bound around the reconstructed time domain waveform.

This paper proposes a low power and high speed track and hold circuit (T/H circuit) based on the two-stage structure. The proposed circuit consists of two internal T/H circuits connected in cascade. The first T/H circuit converts an input signal into a step voltage and it is applied to the following second T/H circuit which drives large load capacitors and consumes large power. Applying the step voltage to the second T/H circuit prevents the second T/H circuit from charging and discharging its load capacitor during an identical track phase and enables low power operation. Thanks to the two-stage structure the proposed T/H circuit can save 29% of the power consumption compared with the conventional one. An optimum design procedure of the proposed two stage T/H circuit is explained and its validity is confirmed by HSPICE simulations.

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

Three-dimensional visualization using jigsaw-puzzle-like glyphs, or shapes, is proposed as a means of representing grammatical constraints in programming. The proposed visualization uses 3D glyphs such as convex, concave, and wireframe shapes. A semantic constraint, such as a type constraint in an assignment, is represented by an inclusive match between 3D glyphs. An application of the proposed visualization method to a subset of the Java programming language is demonstrated. An experimental evaluation showed that the 3D glyphs are easier to learn and enable users to more quickly understand their relationships than 2D glyphs and 1D symbol sequences.

Recent developments in information technology have made it easy for people to "chat" online with others in real time, and many do so regularly. "Virtual" relationships can be attractive, especially for people with social interaction problems in the "real world". This study examines the influence on online chat dependency of three dimensions of social anxiety: general social situation fear, negative evaluation fear, and novel social situation fear. Participants of this study were 454 college students. The survey results show that negative evaluation fear and general social situation fear are relative to online chat dependency, while novel social situation fear does not seem to be a relevant factor.

This paper presents a real-time decision support system (RDSS) based on artificial intelligence (AI) for voltage collapse avoidance (VCA) in power supply networks. The RDSS scheme employs a fuzzy hyperrectangular composite neural network (FHRCNN) to carry out voltage risk identification (VRI). In the event that a threat to the security of the power supply network is detected, an evolutionary programming (EP)-based algorithm is triggered to determine the operational settings required to restore the power supply network to a secure condition. The effectiveness of the RDSS methodology is demonstrated through its application to the American Electric Power Provider System (AEP, 30-bus system) under various heavy load conditions and contingency scenarios. In general, the numerical results confirm the ability of the RDSS scheme to minimize the risk of voltage collapse in power supply networks. In other words, RDSS provides Power Provider Enterprises (PPEs) with a viable tool for performing on-line voltage risk assessment and power system security enhancement functions.

Analysis of resonance frequency in shorted transmission lines with inserted capacitor has been made. The analysis shows a resonance frequency dependence on capacitance position on a shorted transmission line. Two analysis methods are presented to predict the resonance frequency and understand how the inserted capacitor affects the resonance frequency of the shorted transmission line. Using this knowledge we propose a new structure for digital controlled oscillators utilizing the capacitance's sensitivity dependence on position of the shorted transmission line to increase the frequency resolution. A 9 GHz transmission line based digital controlled oscillator was designed and fabricated as a proof of concept. Measured results show that more than 100 times frequency step resolution increase is possible utilizing the same tuning capacitor size located at different points on the transmission line.

We describe a statistical parametric speech synthesis system developed by a joint group from the Nagoya Institute of Technology (Nitech) and the Nara Institute of Science and Technology (NAIST) for the annual open evaluation of text-to-speech synthesis systems named Blizzard Challenge 2006. To improve our 2005 system (Nitech-HTS 2005), we investigated new features such as mel-generalized cepstrum-based line spectral pairs (MGC-LSPs), maximum likelihood linear transform (MLLT), and a full covariance global variance (GV) probability density function (pdf). A combination of mel-cepstral coefficients, MLLT, and full covariance GV pdf scored highest in subjective listening tests, and the 2006 system performed significantly better than the 2005 system. The Blizzard Challenge 2006 evaluations show that Nitech-NAIST-HTS 2006 is competitive even when working with relatively large speech databases.

Two dual-band bandpass filters (BPFs) based on the doubly parallel-coupled stepped impedance resonators (SIRs) structures have been proposed in this paper. The coupled-SIRs with/without open-stub-loads are introduced in the filter design. The dual-band filters exhibiting multiple zeros design operate at 2.45/5.2-GHz for the WLAN applications. Two three-staged filters composed of four SIRs have been proposed with the tapped-line adapted in the I/O sections. A five-staged filter is constructed based on the same design principle to achieve a better band-rejection. The proposed filters have the advantages of a much wider bandwidth in both the passbands without sacrificing the passband's insertion loss and passband flatness. The design procedure for a conventional parallel-coupled microstrip lines model is still suitable to design the proposed filters. The proposed filters have achieved almost twice the bandwidth of a conventional parallel-coupled lines configuration under the same design parameters. The experiments have been conducted to verify filter performance. Measured results are in good agreement with the full-wave simulation results.

A deterministic pushdown automaton (dpda) having just one stack symbol is called a deterministic restricted one-counter automaton (droca). When it accepts an input by empty stack, it is called strict. This paper is concerned with a subclass of real-time strict droca's, called Szilard strict droca's, and studies the problem of identifying the subclass in the limit from positive data. The class of languages accepted by Szilard strict droca's coincides with the class of Szilard languages (or, associated languages) of strict droca's and is incomparable to each of the class of regular languages and that of simple languages. After providing some properties of languages accepted by Szilard strict droca's, we show that the class of Szilard strict droca's is polynomial time identifiable in the limit from positive data in the sense of Yokomori. This identifiability is proved by giving an exact characteristic sample of polynomial size for a language accepted by a Szilard strict droca. The class of very simple languages, which is a proper subclass of simple languages, is also proved to be polynomial time identifiable in the limit from positive data by Yokomori, but it is yet unknown whether there exists a characteristic sample of polynomial size for any very simple language.

In this paper, we propose a two-microphone noise reduction method to deal with non-stationary interfering noises in multiple-noise-source environments in which the traditional two-microphone algorithms cannot function well. In the proposed algorithm, multiple interfering noise sources are regarded as one virtually integrated noise source in each subband, and the spectrum of the integrated noise is then estimated using its virtual direction of arrival. To do this, we suggest a direction finder for the integrated noise using only two microphones that performs well even in speech active periods. The noise spectrum estimate is further improved by integrating a single-channel noise estimation approach and then subtracted from that of the noisy signal, finally enhancing the desired target signal. The performance of the proposed algorithm is evaluated and compared with the traditional algorithms in various conditions. Experimental results demonstrate that the proposed algorithm outperforms the traditional algorithms in various conditions in terms of objective and subjective speech quality measures.