This paper analyzes three passive noise shaping techniques in a SAR ADC. These passive noise shaping techniques can realize 1st and 2nd order noise shaping. These proposed opamp-less noise shaping techniques are realized by charge-redistribution. This means that the proposals maintain the basic architecture and operation principle of a charge-redistribution SAR ADC. Since the proposed techniques work in a passive mode, the proposals have high power efficiency. Meanwhile, the proposed noise shaping SAR ADCs are robust to feature size scaling and power supply reduction. Flicker noise is not introduced into the ADC by passive noise shaping techniques. Therefore, no additional calibration techniques for flicker noise are required. The noise shaping effects of the 1st and 2nd order noise shaping are verified by behavioral simulation results. The relationship between resolution improvement and oversampling rate is also explored in this paper.

The problem of power allocation in maximizing the energy efficiency of the secondary user (SU) in a delay quality-of-service (QoS) constrained CR network is investigated in this paper. The average interference power constraint is used to protect the transmission of the primary user (SU). The energy efficiency is expressed as the ratio of the effective capacity to the total power consumption. By using non-linear fractional programming and convex optimization theory, we develop an energy efficiency power allocation scheme based on the Dinkelbach method and the Lagrange multiplier method. Numerical results show that the proposed scheme outperforms the existing schemes, in terms of energy efficiency.

The dyadic filter bank property of multivariate empirical mode decomposition (MEMD) for white Gaussian noise (WGN) is well established. In order to investigate the way MEMD behaves in the presence of fractional Gaussian noise (fGn), we conduct thorough numerical experiments for MEMD for fGn inputs. It turns out that similar to WGN, MEMD follows dyadic filter bank structure for fGn inputs, which is more stable than empirical mode decomposition (EMD) regardless of the Hurst exponent. Moreover, the estimation of the Hurst exponent of fGn contaminated with different kinds of signals is also presented via MEMD in this work.

In this study we investigate the synchronization of relaxation oscillators having individual differences by using non-periodic signal injection. When a common non-periodic signal is injected into the relaxation oscillators, the oscillators exhibit synchronization phenomena. Such synchronization phenomena can be classified as injection locking. We also consider the relation between the synchronization state and the individual difference. Further, we pay attention to the effect of the fluctuation range of the non-periodic injected signal. When the fluctuation range is wide, we confirm that the synchronization range increases if the individual difference is small.

Fine-grained visual categorization (FGVC) has drawn increasing attention as an emerging research field in recent years. In contrast to generic-domain visual recognition, FGVC is characterized by high intra-class and subtle inter-class variations. To distinguish conceptually and visually similar categories, highly discriminative visual features must be extracted. Moreover, FGVC has highly specialized and task-specific nature. It is not always easy to obtain a sufficiently large-scale training dataset. Therefore, the key to success in practical FGVC systems is to efficiently exploit discriminative features from a limited number of training examples. In this paper, we propose an efficient two-step dimensionality compression method to derive compact middle-level part-based features. To do this, we compare both space-first and feature-first convolution schemes and investigate their effectiveness. Our approach is based on simple linear algebra and analytic solutions, and is highly scalable compared with the current one-vs-one or one-vs-all approach, making it possible to quickly train middle-level features from a number of pairwise part regions. We experimentally show the effectiveness of our method using the standard Caltech-Birds and Stanford-Cars datasets.

In recent years, optical music recognition (OMR) has been extensively developed, particularly for use with mobile devices that require fast processing to recognize and play live the notes in images captured from sheet music. However, most techniques that have been developed thus far have focused on playing back instrumental music and have ignored the importance of lyric extraction, which is time consuming and affects the accuracy of the OMR tools. The text of the lyrics adds complexity to the page layout, particularly when lyrics touch or overlap musical symbols, in which case it is very difficult to separate them from each other. In addition, the distortion that appears in captured musical images makes the lyric lines curved or skewed, making the lyric extraction problem more complicated. This paper proposes a new approach in which lyrics are detected and extracted quickly and effectively. First, in order to resolve the distortion problem, the image is undistorted by a method using information of stave lines and bar lines. Then, through the use of a frequency count method and heuristic rules based on projection, the lyric areas are extracted, the cases where symbols touch the lyrics are resolved, and most of the information from the musical notation is kept even when the lyrics and music notes are overlapping. Our algorithm demonstrated a short processing time and remarkable accuracy on two test datasets of images of printed Korean musical scores: the first set included three hundred scanned musical images; the second set had two hundred musical images that were captured by a digital camera.

This paper proposes an appearance-based novel descriptor for estimating head orientation. Our descriptor is inspired by the Weber-based feature, which has been successfully implemented for robust texture analysis, and the gradient which performs well for shape analysis. To further enhance the orientation differences, we combine them with an analysis of the intensity deviation. The position of a pixel and its intrinsic intensity are also considered. All features are then composed as a feature vector of a pixel. The information carried by each pixel is combined using a covariance matrix to alleviate the influence caused by rotations and illumination. As the result, our descriptor is compact and works at high speed. We also apply a weighting scheme, called Block Importance Feature using Genetic Algorithm (BIF-GA), to improve the performance of our descriptor by selecting and accentuating the important blocks. Experiments on three head pose databases demonstrate that the proposed method outperforms the current state-of-the-art methods. Also, we can extend the proposed method by combining it with a head detection and tracking system to enable it to estimate human head orientation in real applications.

Key frame based video summarization has emerged as an important task for efficient video data management. This paper proposes a novel technique for key frame extraction based on chaos theory and color information. By applying chaos theory, a large content change between frames becomes more chaos-like and results in a more complex fractal trajectory in phase space. By exploiting the fractality measured in the phase space between frames, it is possible to evaluate inter-frame content changes invariant to effects of fades and illumination change. In addition to this measure, the color histogram-based measure is also used to complement the chaos-based measure which is sensitive to changes of camera /object motion. By comparing the last key frame with the current frame based on the proposed frame difference measure combining these two complementary measures, the key frames are robustly selected even under presence of video fades, changes of illumination, and camera/object motion. The experimental results demonstrate its effectiveness with significant improvement over the conventional method.

In this paper, we investigate a preference-aware multicast mechanism in active array aided LTE (Long Term Evolution) networks. An active antenna system can direct vertical beams in different horizontal and vertical directions, so the amount of energy delivered is more concentrated on the target users. The active array provides each multicast group with an individual beam with specific downtilt delivering shared video to all users in the group. For the multicast system, the objective of our proposed resource allocation scheme is to maximize the total throughput, subject to the constraints of power, subcarrier and antenna downtilt, as well as horizontal angles and the vertical half power bandwidth. To solve the problem, individual beams are steered for multicast groups. Furthermore, a novel subcarrier assignment scheme is proposed to enhance the spectrum resource utilization, and the optimal power allocation is obtained by virtue of Lagrangian method. Simulation results demonstrate the throughput and the spectral efficiency enhancement of our proposed scheme over other conditional schemes.

Considering the obvious bias of the traditional interpolation method, a novel time delay estimation (TDE) interpolation method with sub-sample accuracy is presented in this paper. The proposed method uses a generalized extended approximation method to obtain the objection function. Then the optimized interpolation curve is generated by Second-order Cone programming (SOCP). Finally the optimal TDE can be obtained by interpolation curve. The delay estimate of proposed method is not forced to lie on discrete samples and the sample points need not to be on the interpolation curve. In the condition of the acceptable computation complexity, computer simulation results clearly indicate that the proposed method is less biased and outperforms the other interpolation algorithms in terms of estimation accuracy.

Residents living in a nursing home usually have established medical histories in multiple sources, and most previous medicine management systems have only focused on the integration of prescriptions and the identification of repeated drug uses. Therefore, a comprehensive medicine management system is proposed to integrate medical information from different sources. The proposed system not only detects inappropriate drugs automatically but also allows users to input such information for any non-prescription medicines that the residents take. Every participant can fully track the residents' latest medicine use online and in real time. Pharmacists are able to issue requests for suggestions on medicine use, and residents can also have a comprehensive understanding of their medicine use. The proposed scheme has been practically implemented in a nursing home in Taiwan. The evaluation results show that the average time to detect an inappropriate drug use and complete a medicine record is reduced. With automatic and precise comparisons, the repeated drugs and drug side effects are identified effectively such that the amount of medicine cost spent on the residents is also reduced. Consequently, the proactive feedback, real-time tracking, and interactive consulting mechanisms bind all parties together to realize a comprehensive medicine management system.

We describe a calculation tool and modeling methods to find self and mutual inductance and current distribution in superconductive multilayer circuit layouts. Accuracy of the numerical solver is discussed and compared with experimental measurements. Effects of modeling parameter selection on calculation results are shown, and we make conclusions on the selection of modeling parameters for fast but sufficiently accurate calculations when calibration methods are used. Circuit theory for the calculation of branch impedances from the output of the numerical solver is discussed, and compensation for solution difficulties is shown through example. We elaborate on the construction of extraction models for superconductive integrated circuits, with and without resistive branches. We also propose a method to calculate current distribution in a multilayer circuit with multiple bias current feed points. Finally, detailed examples are shown where the effects of stacked vias, bias pillars, coupling, ground connection stacks and ground return currents in circuit layouts for the AIST advanced process (ADP2) and standard process (STP2) are analyzed. We show that multilayer inductance and current distribution extraction in such circuits provides much more information than merely branch inductance, and can be used to improve layouts; for example through reduced coupling between conductors.

A method for increasing alignment tolerance in simple multiple-stream transmission is described. Its use of π-shifted antenna directivity phase enables it to cancel interference even when antenna placement deviations occur. The interference cancellation by using π-shifted directivities provides higher alignment tolerance than that with conventional fixed weight methods. It also provides smaller channel gain variation than can be obtained using fixed weights even when antenna displacement occurs. An objective function is described that is determined by the alignment tolerance. The function is defined to maximize the alignment tolerance. The method's validity is confirmed by an experimental analysis of two-stream transmission in which the alignment tolerance of the proposed method is compared to that of conventional fixed weight methods.

This paper considers an optimal stabilization problem of quantitative discrete event systems (DESs) under the influence of disturbances. We model a DES by a deterministic weighted automaton. The control cost is concerned with the sum of the weights along the generated trajectories reaching the target state. The region of weak attraction is the set of states of the system such that all trajectories starting from them can be controlled to reach a specified set of target states and stay there indefinitely. An optimal stabilizing controller is a controller that drives the states in this region to the set of target states with minimum control cost and keeps them there. We consider two control objectives: to minimize the worst-case control cost (1) subject to all enabled trajectories and (2) subject to the enabled trajectories starting by controllable events. Moreover, we consider the disturbances which are uncontrollable events that rarely occur in the real system but may degrade the control performance when they occur. We propose a linearithmic time algorithm for the synthesis of an optimal stabilizing controller which is robust to disturbances.

Vector data differs in the rasterized height field by data type. It is difficult to render dynamic vectors on height field because their shapes and locations may change at any time. This letter proposes a novel method: View-dependent Projective Atlases (VdPAs). As an intermediate data source, VdPAs act as rendering targets which enable height field and vectors to be rasterized at the same resolution. Then, VdPAs can be viewed as super-tiles. State of art height field rendering algorithms can be used for scenario rendering. Experimental results demonstrate that atlases are able to make dynamic vectors to be rendered on height field with real-time performance and high quality.

This paper proposes a high clutter-rejection technique for wall-penetrating frequency-modulated continuous-wave (FMCW) radar. FMCW radars are widely used, as they moderate the receiver saturation problem in wall-penetrating applications by attenuating short-range clutter such as wall-clutter. However, conventional FMCW radars require a very high-order high-pass filter (HPF) to attenuate short-range clutter. A delay-line (DL) is exploited to overcome this problem. Time-delay shifts beat frequencies formed by reflection waves. This means that a proper time-delay increases the ratio of target-beat frequency to clutter-beat frequency. Consequently, low-order HPF fully attenuates short-range clutter. A third-order HPF rejects more than 20 dB and 30 dB for clutter located at 6 m and 3 m, respectively, with a target located at 9 m detection with a 10,000 GHz/s chirp rate and a 28 ns delay-line.

An application of laser annealing process, which is used to form the shallow P-type Base junction for 20-V planar power MOSFETs (Metal Oxide Semiconductor Field Effect Transistors) is proposed. We demonstrated that the fabricated devices integrated with laser annealing process have superior electrical characteristics than those fabricated according to the standard process. Moreover, the threshold voltage variation of the devices applied by the new annealing process is effectively suppressed. This is due to that a uniform impurity distribution at the channel region is achieved by adopting laser annealing. Laser annealing technology can be applied as a reliable, effective, and advantageous process for the low-voltage power MOSFETs.

This paper investigates current-gain and high-frequency characteristics of double heterojunction bipolar transistors (DHBTs) with a uniform GaAsSb, compositionally graded GaAsSb, uniform InGaAsSb, or compositionally graded InGaAsSb base. DHBTs with a compositionally graded InGaAsSb base exhibit a high current gain of ∼75 and fT=504GHz. In order to boost fmax of DHBTs with a compositionally graded InGaAsSb base, a highly doped GaAsSb base contact layer is inserted. The fabricated DHBTs exhibit fT/fmax=513/637GHz and a breakdown voltage of 5.2V.

Maneuvering target tracking under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions has received considerable interest in the last decades. In this paper, a hierarchical interacting multiple model (HIMM) method is proposed for estimating target position under mixed LOS/NLOS conditions. The proposed HIMM is composed of two layers with Markov switching model. The purpose of the upper layer, which is composed of two interacting multiple model (IMM) filters in parallel, is to handle the switching between the LOS and the NLOS environments. To estimate the target kinetic variables (position, speed and acceleration), the unscented Kalman filter (UKF) with the current statistical (CS) model is used in the lower-layer. Simulation results demonstrate the effectiveness and superiority of the proposed method, which obtains better tracking accuracy than the traditional IMM.

This study proposes the application and implementation of a new power factor correction (PFC) with a variable slope ramp for a small wind power system without any input voltage sensing circuits or external control components in the current shaping loop. The hardware description of the variable slope ramp simplifies the complexity of integrated circuit realization with low resolution analog-to-digital converters, and achieves a high power factor for multi and three-phase AC/DC converters such as wind power systems. Up to 1 kW small wind power system is tested to verify the performance of the proposed PFC control. The highest achieved power factor reaches 99.5%.