Traditional two-microphone noise reduction algorithms to deal with highly nonstationary directional noises generally use the direction of arrival or phase difference information. The performance of these algorithms deteriorate when diffuse noises coexist with nonstationary directional noises in realistic adverse environments. In this paper, we present a two-channel noise reduction algorithm using a spatial information-based speech estimator and a spatial-information-controlled soft-decision noise estimator to improve the noise reduction performance in realistic non-stationary noisy environments. A target presence probability estimator based on Bayes rules using both phase difference and magnitude squared coherence is proposed for soft-decision of noise estimation, so that they can share complementary advantages when both directional noises and diffuse noises are present. Performances of the proposed two-microphone noise reduction algorithm are evaluated by noise reduction, log-spectral distance (LSD) and word recognition rate (WRR) of a distant-talking ASR system in a real room's noisy environment. Experimental results show that the proposed algorithm achieves better noises suppression without further distorting the desired signal components over the comparative dual-channel noise reduction algorithms.

Electrical performances of gate-all-around (GAA) tunneling field-effect transistors (TFETs) based on a silicon germanium (Si1-xGex) layer have been investigated in terms of subthreshold swing (SS), on/off current ratio, on-state current (Ion). Cut-off frequency (fT) and maximum oscillation frequency (fmax) were demonstrated from small-signal parameters such as effective gate resistance (Rg), gate-drain capacitance (Cgd), and transconductance (gm). According to the technology computer-aided design (TCAD) simulation results, the current drivability, fT, and fmax of GAA TFETs based on Si1-xGex layer were higher than those of GAA TFETs based on silicon. The simulated devices had 60 nm channel length and 10 nm channel radius. A GAA TFET with x = 0.4 had maximum Ion of 51.4 µA/µm, maximum fT of 72 GHz, and maximum fmax of 610 GHz. Additionally, improvements of performance at the presented device with PNPN junctions were demonstrated in terms of Ion, SS, fT, and fmax. When the device was designed with x = 0.4 and n+ layer width (Wn) = 6 nm, it shows Ion of 271 µA/µm, fT of 245 GHz, and fmax of 1.49 THz at an operating bias (VGS = VDS = 1.0 V).

Spatial Multiplexing with precoding provides an opportunity to enhance the capacity and reliability of multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. However, precoder selection may require knowledeg of all subcarriers, which may cause a large amount of feedback if not properly designed. In addition, if the maximum-likelihood (ML) detector is employed, the conventional precoder selection that maximizes the minimum stream SNR is not optimal in terms of the error probability. In this paper, we propose to reduce the feedback overhead by introducing a ML clustering concept in selecting the optimal precoder for ML detector. Numerical results show that the proposed precoder selection based on the ML clustering provides enhanced performance for ML receiver compared with conventional interpolation and clustering algorithms.

By performing the encoding operation on several message packets, rateless coding in cooperative networks has the potential risk of processing information already available to the receivers. In this paper, the intermediate packet decodability of rateless codes is exploited to mitigate such redundant packet processing at the cooperating nodes. The message packets that are already decoded at the receivers are eliminated from further processing by harnessing the back channel (from receiver to transmitter) for feedback. This reduces the required number of transmissions and optimizes the throughput of the network.

The traffic adaptive 2-level active period control has been proposed as a traffic adaptation mechanism to handle temporal and spatial (geographical) traffic fluctuations in cluster-based wireless sensor networks (WSNs) employing IEEE802.15.4 medium access control (MAC). This paper proposes a traffic adaptive distributed backoff control mechanism for cluster-based WSNs with the traffic adaptive 2-level active period control to enhance the system performance, especially transmission performance. The proposed mechanism autonomously adjusts the starting time of the backoff procedure for channel accesses in the contention access period (CAP) specified by the IEEE802.15.4 MAC, and then distributes the channel access timing over a wide range within the CAP, which can mitigate channel access congestion. The results of computer simulations show that the proposed mechanism can improve the transmission delay performance while keeping the enhancement in throughput and energy consumption at the cluster-based WSNs under non-uniform traffic environments.

In this paper, Source/Drain (S/D) engineering for high performance (HP) Vertical MOSFET (V-MOSFET) in 3Xnm generation and its beyond is investigated, by using gradual S/D profile while degradation of driving current (ION) due to the parasitic series resistance (Rpara) is minimized through two-dimensional device simulation taking into account for gate-induced-drain-leakage (GIDL). In general, it is significant to reduce spreading resistance in the case of conventional Planar MOSFET. Therefore, in this study, we focused and analyzed the abruptness of diffusion layer that is still importance parameter in V-MOSFET. First, for improving the basic device performance such as subthreshold swing (SS), ION, and Rpara, S/D engineering is investigated. The dependency of device performance on S/D abruptness (σS/D) for various Lightly Doped Drain Extension (LDD) abruptness (σLDD) is analyzed. In this study, Spacer Length (LSP) is defined as a function of σS/D. As σS/D becomes smaller and S/D becomes more abrupt, LSP becomes shorter. SS depends on the σS/D rather than the σLDD. ION has the peak value of 1750 µA/µm at σS/D = 2 nm/dec. and σLDD=3 nm/dec. when the silicon pillar diameter (D) is 30 nm and the gate length (Lg) is 60 nm. As σS/D becomes small, higher ION is obtained due to reduction of Rpara while SS is degraded. However, when σS/D becomes too small in the short channel devices (Lg = 60 nm and Lg = 45 nm), ION is degraded because the leakage current due to GIDL is increased and reaches IOFF limit of 100 nA/µm. In addition, as σLDD becomes larger, larger ION is obtained in the case of Lg = 100 nm and Lg = 60 nm because channel length becomes shorter. On the other hand, in the case of Lg = 45 nm, as σLDD becomes larger, ION is degraded because short channel effect (SCE) becomes significant. Next, the dependency of the basic device performance on D is investigated. By slimming D from 30 nm to 10 nm, while SS is improved and approaches the ideal value of 60 mV/Decade, ION is degraded due to increase of on-resistance (Ron). From these results, it is necessary to reduce Rpara while IOFF meets limit of 100 nA/µm for designing S/D of HP V-MOSFET. Especially for the V-MOSFET in the 1Xnm generation and its beyond, the influence of the Rpara and GIDL on ION becomes more significant, and therefore, the trade-off between σS/D and ION has a much greater impact on S/D engineering of V-MOSFET.

In this work we propose a novel smart card based privacy-protecting authentication scheme for roaming services. Our proposal achieves so-called Class 2 privacy protection, i.e., no information identifying a roaming user and also linking the user's behaviors is not revealed in a visited network. It can be used to overcome the inherent structural flaws of smart card based anonymous authentication schemes issued recently. As shown in our analysis, our scheme is computationally efficient for a mobile user.

In order to improve the address discharge characteristics, we propose the modified selective reset waveform utilizing the address-bias voltage (Va-bias) during the ramp-up period. It is revealed that the proper Va-bias makes the weak discharge between the address and scan electrodes which plays a role in sufficiently removing the wall charge, thereby contributing to minimizing the wall-voltage variation during the address-period. As a result of adopting the Va-bias in the conventional selective reset driving waveform, it was found that the address discharge delay time can be shortened by approximately 40 ns and the address period of each subfield can be significantly reduced by about 43 µs.

Acoustic data transmission is a technique which embeds data in a sound wave imperceptibly and detects it at a receiver. The data are embedded in an original audio signal and transmitted through the air by playing back the data-embedded audio using a loudspeaker. At the receiver, the data are extracted from the received audio signal captured by a microphone. In our previous work, we proposed an acoustic data transmission system designed based on phase modification of the modulated complex lapped transform (MCLT) coefficients. In this paper, we propose the spectral magnitude adjustment (SMA) technique which not only enhances the quality of the data-embedded audio signal but also improves the transmission performance of the system.

We have studied resistance-switching properties of RF sputtered Si-rich oxides sandwiching with Pt electrodes. By sweeping bias to the top Pt electrode, non-polar type resistance switching was observed after a forming process. In comparison to RF sputtered TiOx case, significant small current levels were obtained in both the high resistance state (HRS) and the low resistance state (LRS). And, even with decreasing SiOx thickness down to 8 nm from 40 nm, the ON/OFF ratio in resistance-switching between HRS and LRS as large as 103 was maintained. From the analysis of current-voltage characteristics for Pt/SiOx on p-type Si(100) and n-type Si(100), it is suggested that the red-ox (REDction and OXidation) reaction induced by electron fluence near the Pt/SiOx interface is of importance for obtaining the resistance-switching behavior.

In this paper, we propose an interleaving updating framework of disparity and confidence map (IUFDCM) for stereo matching to eliminate the redundant and interfere information from unreliable pixels. Compared with other propagation algorithms using matching cost as messages, IUFDCM updates the disparity map and the confidence map in an interleaving manner instead. Based on the Confidence-based Support Window (CSW), disparity map is updated adaptively to alleviate the effect of input parameters. The reassignment for unreliable pixels with larger probability keeps ground truth depending on reliable messages. Consequently, the confidence map is updated according to the previous disparity map and the left-right consistency. The top ranks on Middlebury benchmark corresponding to different error thresholds demonstrate that our algorithm is competitive with the best stereo matching algorithms at present.

Cognitive radios are intelligent communications, and are expected to more efficiently utilize the radio channel. Modulation identification is one of the key issues in the cognitive radios. Many works were devoted to the classification of symbol-by-symbol modulations, however, few papers on block modulations have been published. In this paper, an identification error analysis is presented for block orthogonal modulations using General Orthogonal Modulation~(GOM). A symbol error probability is derived for the identified block orthogonal modulation. Numerical results of 4-dimensional block orthogonal modulation are presented with simulation results.

In this letter, we propose a novel resource allocation scheme to enhance downlink system performance for orthogonal frequency division multiple access (OFDMA) and time division duplex (TDD) based femtocell networks. In the proposed scheme, the macro base station (mBS) and femto base stations (fBSs) service macro user equipments (mUEs) and femto user equipments (fUEs) in inner and outer zones in different periods to reduce interference substantially. Simulations show the proposed scheme outperforms femtocell networks with fractional frequency reuse (FFR) systems in terms of the system capacity and outage probability for mUEs and fUEs.

This paper presents an efficient algorithm, NEAR, that allows sensor nodes to acquire their off-duty eligibility. Any node only needs to calculate the coverage degrees of the intersections on its sensing boundary, and cooperates with its neighbors to know if it is redundant or not. The computing complexity of NEAR is only O(nlogn).

Polar and Spherical Fourier analysis can be used to extract rotation invariant features for image retrieval and pattern recognition tasks. They are demonstrated to show superiorities comparing with other methods on describing rotation invariant features of two and three dimensional images. Based on mathematical properties of trigonometric functions and associated Legendre polynomials, fast algorithms are proposed for multimedia applications like real time systems and large multimedia databases in order to increase the computation speed. The symmetric points are computed simultaneously. Inspired by relative prime number theory, systematic analysis are given in this paper. Novel algorithm is deduced that provide even faster speed. Proposed method are 9–15% faster than previous work. The experimental results on two and three dimensional images are given to illustrate the effectiveness of the proposed method. Multimedia signal processing applications that need real time polar and spherical Fourier analysis can be benefit from this work.

We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

In this paper, we propose a novel approach for presenting the local features of digital image using 1D Local Patterns by Multi-Scans (1DLPMS). We also consider the extentions and simplifications of the proposed approach into facial images analysis. The proposed approach consists of three steps. At the first step, the gray values of pixels in image are represented as a vector giving the local neighborhood intensity distrubutions of the pixels. Then, multi-scans are applied to capture different spatial information on the image with advantage of less computation than other traditional ways, such as Local Binary Patterns (LBP). The second step is encoding the local features based on different encoding rules using 1D local patterns. This transformation is expected to be less sensitive to illumination variations besides preserving the appearance of images embedded in the original gray scale. At the final step, Grouped 1D Local Patterns by Multi-Scans (G1DLPMS) is applied to make the proposed approach computationally simpler and easy to extend. Next, we further formulate boosted algorithm to extract the most discriminant local features. The evaluated results demonstrate that the proposed approach outperforms the conventional approaches in terms of accuracy in applications of face recognition, gender estimation and facial expression.

Nowadays, clustering is a popular tool for exploratory data analysis, with one technique being K-means clustering. Determining the appropriate number of clusters is a significant problem in K-means clustering because the results of the k-means technique depend on different numbers of clusters. Automatic determination of the appropriate number of clusters in a K-means clustering application is often needed in advance as an input parameter to the K-means algorithm. We propose a new method for automatic determination of the appropriate number of clusters using an extended co-occurrence matrix technique called a tri-co-occurrence matrix technique for multispectral imagery in the pre-clustering steps. The proposed method was tested using a dataset from a known number of clusters. The experimental results were compared with ground truth images and evaluated in terms of accuracy, with the numerical result of the tri-co-occurrence providing an accuracy of 84.86%. The results from the tests confirmed the effectiveness of the proposed method in finding the appropriate number of clusters and were compared with the original co-occurrence matrix technique and other algorithms.