We present a new lower bound on the number of gates in reversible logic circuits that represent a given reversible logic function, in which the circuits are assumed to consist of general Toffoli gates and have no redundant input/output lines. We make a theoretical comparison of lower bounds, and prove that the proposed bound is better than the previous one. Moreover, experimental results for lower bounds on randomly-generated reversible logic functions and reversible benchmarks are given. The results also demonstrate that the proposed lower bound is better than the former one.

The excessively high temperature in a chip may cause circuit malfunction and performance degradation, and thus should be avoided to improve system reliability. In this paper, a novel oscillation-based on-chip thermal sensing architecture for dynamically adjusting supply voltage and clock frequency in System-on-a-Chip (SoC) is proposed. It is shown that the oscillation frequency of a ring oscillator reduces linearly as the temperature rises, and thus provides a good on-chip temperature sensing mechanism. An efficient Dynamic Voltage-to-Frequency Scaling (DF2VS) algorithm is proposed to dynamically adjust supply voltage according to the oscillation frequencies of the ring oscillators distributed in SoC so that thermal sensing can be carried at all potential hot spots. An on-chip Dynamic Voltage Scaling or Dynamic Voltage and Frequency Scaling (DVS or DVFS) monitor selects the supply voltage level and clock frequency according to the outputs of all thermal sensors. Experimental results on SoC benchmark circuits show the effectiveness of the algorithm that a 10% reduction in supply voltage alone can achieve about 20% power reduction (DVS scheme), and nearly 50% reduction in power is achievable if the clock frequency is also scaled down (DVFS scheme). The chip temperature will be significant lower due to the reduced power consumption.

A novel Two-dimensional Fuzzy Discriminant Locality Preserving Projections (2D-FDLPP) algorithm is proposed for learning effective subspace of two-dimensional images. The 2D-FDLPP algorithm is derived from the Two-dimensional Locality Preserving Projections (2D-LPP) by exploiting both fuzzy and discriminant properties. 2D-FDLPP algorithm preserves the relationship degree of each sample belonging to given classes with fuzzy k-nearest neighbor classifier. Also, it introduces between-class scatter constrain and label information into 2D-LPP algorithm. 2D-FDLPP algorithm finds the subspace which can best discriminate different pattern classes and weakens the environment factors according to soft assignment method. Therefore, 2D-FDLPP algorithm has more discriminant power than 2D-LPP, and is more suitable for recognition tasks. Experiments are conducted on the MNIST database for handwritten image classification, the JAFFE database and Cohn-Kanade database for facial expression recognition and the ORL database for face recognition. Experimental results reported the effectiveness of our proposed algorithm.

A major challenge for speech emotion recognition is that when the training and deployment conditions do not use the same speech corpus, the recognition rates will obviously drop. Transfer learning, which has successfully addressed the cross-domain classification or recognition problem, is presented for cross-corpus speech emotion recognition. First, by using the maximum mean discrepancy embedding (MMDE) optimization and dimension reduction algorithms, two close low-dimensional feature spaces are obtained for source and target speech corpora, respectively. Then, a classifier function is trained using the learned low-dimensional features in the labeled source corpus, and directly applied to the unlabeled target corpus for emotion label recognition. Experimental results demonstrate that the transfer learning method can significantly outperform the traditional automatic recognition technique for cross-corpus speech emotion recognition.

A directional array radiator is presented, the aim of which is to enhance the sound of the television in a particular direction and hence provide a volume boost to improve speech intelligibility for the hard of hearing. The sound radiated by the array in other directions is kept low, so as not to increase the reverberant level of sound in the listening room. The array uses 32 loudspeakers, each of which are in phase-shift enclosures to generate hypercardioid directivity, which reduces the radiation from the back of the array. The loudspeakers are arranged in 8 sets of 4 loudspeakers, each set being driven by the same signal and stacked vertically, to improve the directivity in this plane. This creates a 3D beamformer that only needs 8 digital filters to be made superdirective. The performance is assessed by means of simulations and measurements in anechoic and reverberant environments. The results show how the array obtains a high directivity in a reverberant environment.

Positive real approximation of sampled frequency data obtained from electromagnetic analysis or measurement is presented. The proposed two methods are based on the Fourier expansion method. The frequency data are approximated by the Laguerre series that becomes the Fourier series with an infinite interval at an imaginary axis of complex plane. The proposed methods do not require any passivity check algorithm. The first method approximates the real parts of sampled data by the piecewise linear matrix function. The second method uses discrete Fourier transform. It is here proven that the approximated matrix function is an interpolative function for the real parts of sampled data. The proposed methods are applied to the approximation of per unit length parameters of multi-conductor system. The capability of the proposed methods is demonstrated.

This study introduces an image sensor based visible light communication (VLC) and its application to pose, position, and range estimations. There are two types of visible-light receiver: a photodiode and an image sensor. A photodiode is usually used as a reception device of VLC, and an image sensor consisting of a large number of pixels can also be used as a VLC reception device. A photodiode detects the signal intensity of incoming light, while an image sensor not only detects the incoming signal intensity but also an accurate angle of arrival of light emitted from a visible light transmitter such as a white LED light. After angles of arrival of light are detected by an image sensor, positioning and data reception can be performed. The ability of an image sensor to detect an accurate angle of arrival will provide attractive applications of VLC such as pose, position calculation, and range estimation. Furthermore, because the image sensor has the ability to spatially separate sources, outdoor positioning even with strong sunlight is possible by discarding the associated pixels of noise sources.

A global tree local X-net network (GTLX) is introduced to realize high-performance data transfer in a multiple-valued fine-grain reconfigurable VLSI (MVFG-RVLSI). A global pipelined tree network is utilized to realize high-performance long-distance bit-parallel data transfer. Moreover, a logic-in-memory architecture is employed for solving data transfer bottleneck between a block data memory and a cell. A local X-net network is utilized to realize simple interconnections and compact switch blocks for eight-near neighborhood data transfer. Moreover, multiple-valued signaling is utilized to improve the utilization of the X-net network, where two binary data can be transferred from two adjacent cells to one common adjacent cell simultaneously at each “X” intersection. To evaluate the MVFG-RVLSI, a fast Fourier transform (FFT) operation is mapped onto a previous MVFG-RVLSI using only the X-net network and the MVFG-RVLSI using the GTLX. As a result, the computation time, the power consumption and the transistor count of the MVFG-RVLSI using the GTLX are reduced by 25%, 36% and 56%, respectively, in comparison with those of the MVFG-RVLSI using only the X-net network.

In the optimization of decision diagrams, variable reordering approaches are often used to minimize the number of nodes. However, such approaches are less effective for analysis of multi-state systems given by monotone structure functions. Thus, in this paper, we propose algorithms to minimize the number of edges in an edge-valued multi-valued decision diagram (EVMDD) for fast analysis of multi-state systems. The proposed algorithms minimize the number of edges by grouping multi-valued variables into larger-valued variables. By grouping multi-valued variables, we can reduce the number of nodes as well. To show the effectiveness of the proposed algorithms, we compare the proposed algorithms with conventional optimization algorithms based on a variable reordering approach. Experimental results show that the proposed algorithms reduce the number of edges by up to 15% and the number of nodes by up to 47%, compared to the conventional ones. This results in a speed-up of the analysis of multi-state systems by about three times.

In this paper, we propose a novel method for road sign detection and recognition in complex scene real world images. Our algorithm consists of four basic steps. First, we employ a regional contrast based bottom-up visual saliency method to highlight the traffic sign regions, which usually have dominant color contrast against the background. Second, each type of traffic sign has special color distribution, which can be explored by top-down visual saliency to enhance the detection precision and to classify traffic signs into different categories. A bag-of-words (BoW) model and a color name descriptor are employed to compute the special-class distribution. Third, the candidate road sign blobs are extracted from the final saliency map, which are generated by combining the bottom-up and the top-down saliency maps. Last, the color and shape cues are fused in the BoW model to express blobs, and a support vector machine is employed to recognize road signs. Experiments on real world images show a high success rate and a low false hit rate and demonstrate that the proposed framework is applicable to prohibition, warning and obligation signs. Additionally, our method can be applied to achromatic signs without extra processing.

The IEEE 802.11 distributed coordinated function (DCF) adopts carrier sense multiple access with collision avoidance (CSMA/CA) as its medium access control (MAC) protocol. In a wireless local area network (WLAN) stations (STAs) congested situation, the performance of the WLAN system is significantly degraded due to a collision between the STAs. In this paper, we propose a simple method that decreases the number of frame collisions. After a successful transmission, the proposed method refrains from transmission during certain time which is defined as post-inter-frame space (Post-IFS). This mechanism improves the system performance including the throughput characteristics and access delay by reducing the number of competing STAs. The length of the Post-IFS is a key factor in improving the system performance for the proposed method. If the access point (AP) can estimate the optimal value of the Post-IFS, collision-free operation similar to that in centralized control is performed. Even if the optimal Post-IFS is not estimated, the number of competing STAs and the collision probability are decreased. Computer simulations verify that the proposed method achieves 40% higher system throughput compared to the conventional CSMA/CA for a network with 50 STAs.

This paper describes a soft-error tolerant and margin-enhanced nMOS-pMOS reversed 6T SRAM cell. The 6T SRAM bitcell comprises pMOS access and driver transistors, and nMOS load transistors. Therefore, the nMOS and pMOS masks are reversed in comparison with those of a conventional bitcell. In scaled process technology, The pMOS transistors present advantages of small random dopant fluctuation, strain-enhanced saturation current, and small soft-error sensitivity. The four-pMOS and two-nMOS structure improves the soft-error rate plus operating margin. We conduct SPICE and neutron-induced soft-error simulations to evaluate the n-p reversed 6T SRAM bitcell in 130-nm to 22-nm processes. At the 22-nm node, a multiple-cell-upset and single-bit-upset SERs are improved by 34% and 51% over a conventional 6T cell. Additionally, the static noise margin and read cell current are 2.04× and 2.81× improved by leveraging the pMOS benefits.

The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amyotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. In this paper, we introduce the gaze estimation system of electrooculogram signals. Using this system, the electrooculogram signals can be recorded when the patients focused on each direct. All these recorded signals could be analyzed using math-method and the mathematical model will be set up. Gaze estimation can be recognized using electrooculogram signals follow these models.

Differential games are considered an extension of optimal control problems, which are used to formulate centralized control problems in smart grids. Optimal control theory is used to study systems consisting of one agent with one objective, whereas differential games are used to formulate systems consisting of multiple agents with multiple objectives. Therefore, a differential-game-theoretic approach is appropriate for formulating decentralized demand-side energy management systems where there are multiple decision-making entities interacting with each other. Moreover, in many smart grid applications, we need to obtain information for control via communication systems. To formulate the influence of communication availability, differential game theory is also promising because the availability of communication is considered as part of an information structure (i.e., feedback or open-loop) in differential games. The feedback information structure is adopted when information for control can be obtained, whereas the open-loop information structure is applied when the information cannot be obtained because of communication failure. This paper proposes a comprehensive framework for evaluating the performance of demand-side actors in a demand-side management system using each control scheme according to both communication availability and sampling frequency. Numerical analysis shows that the proposed comprehensive framework allows for an analysis of trade-off for decentralized and centralized control schemes.

This paper proposes a robust and fast lyric search method for music information retrieval (MIR). The effectiveness of lyric search systems based on full-text retrieval engines or web search engines is highly compromised when the queries of lyric phrases contain incorrect parts due to mishearing. To improve the robustness of the system, the authors introduce acoustic distance, which is computed based on a confusion matrix of an automatic speech recognition experiment, into Dynamic-Programming (DP)-based phonetic string matching to identify the songs that the misheard lyric phrases refer to. An evaluation experiment verified that the search accuracy is increased by 4.4% compared with the conventional method. Furthermore, in this paper a two-pass search algorithm is proposed to realize real-time execution. The algorithm pre-selects the probable candidates using a rapid index-based search in the first pass and executes a DP-based search process with an adaptive termination strategy in the second pass. Experimental results show that the proposed search method reduced processing time by more than 86.2% compared with the conventional methods for the same search accuracy.

Feedback data loss can severely degrade overall system performance. In addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications that include different data traffic patterns. These data traffic patterns have wide varieties of diversities. To recover various traffic patterns we need to know the nature of their underlying property. In this paper, we propose a data recovery framework for different traffic patterns of CPS, which comprises data pre-processing step. In the proposed framework, we designed a Data Pattern Analyzer to classify the different patterns and built a model based on the pattern as a data pre-processing step. Inside the framework, we propose a data recovery scheme, called Efficient Temporal and Spatial Data Recovery (ETSDR) algorithm to recover the incomplete feedback for CPS to maintain real time control. In this algorithm, we utilize the temporal model based on the traffic pattern and consider the spatial correlation of the nearest neighbor sensors. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithms regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.

In this paper, a new analog signal transmission technique called analog single-carrier transmission with frequency-domain equalization (analog SC-FDE) is proposed. Analog SC-FDE applies discrete Fourier transform (DFT), frequency-domain spectrum shaping and mapping, inverse DFT (IDFT), and cyclic prefix (CP) insertion before transmission. At the receiver, one-tap FDE is applied to take advantage of frequency diversity. This paper considers, as an example, analog voice transmission. A theoretical analysis of the normalized mean square error (NMSE) performance is carried out to evaluate the transmission property of the proposed analog SC-FDE and is confirmed by computer simulation. We show that analog SC-FDE achieves better NMSE performance than conventional analog signal transmission scheme.

Wide area virtualization of wireless transceivers by centrally managed software radio systems is a way to efficiently share the resources for supporting a variety of wireless protocols. In order to enable wide-area virtualization of wireless transceivers, the authors have developed a mechanism to deliver the radio space information which is quantized broadband radio wave information including the radio signals to the transceivers. Delivery mechanism consists of a distribution server which distributes radio space corresponding to the request of the client such as the center frequency and the bandwidth and a client which uses the radio space information. Accumulation of the distribution servers which deliver radio space information simultaneously to a large number of clients will contribute to build an infrastructure for any clients ubiquitously distributed over the globe. In this paper, scale-out architecture of a distribution server is proposed to deliver unlimitedly broadband radio space information to unlimited number of clients. Experimental implementation indicates the architecture to be a scale-out solution, while the number of clients is restricted by the computer resources of the distribution server. The band pass filter processing for individual client in the distribution server consumes the dominant part of the processing power, and the number of CPU cores is the upper limit of clients supportable for the distribution server in the current operating system implementation. The logical increase of the number of CPU cores by hardware multithreading does not contribute to relax this limit. We also discuss the guidance architecture or building server derived from these conclusions.

An accurate time-of-arrival (TOA) estimation method for isolated pulses positioning system is proposed in this paper. The method is based on a multi-level crossing timing (MCT) digitizer and least square (LS) criterion, namely LS-MCT method, in which TOA of the received signal is directly described as a parameterized combination of a set of MCT samples of the leading and trailing edges of the signal. The LS-MCT method performs a receiver training process, in which a GPS synchronized training pulse generator (TPG) is used to obtain training data and determine the parameters of the TOA combination. The LS method is then used to optimize the combination parameters with a minimization criterion. The proposed method is compared to the conventional TOA estimation methods such as leading edge level crossing discriminator (LCD), adaptive thresholding (ATH), and signal peak detection (PD) methods. Simulation results show that the proposed algorithm leads to lower sensitivity to signal-to-noise ratio (SNR) and attains better TOA estimation accuracy than available TOA methods.

Recently, radar resource management of multifunction radar is a challenging issue in electronically scanned array radar technology. This paper deals with radar beam scheduling, which is a core issue of radar resource management. This paper proposed stochastic scheduler algorithm using Simulated Annealing (SA) and Hybrid scheduler algorithm which automatically selects two different types of schedulers according to the radar load: Rule based scheduler using modified Butler algorithm for underload situations and SA based scheduler for overload situations. The proposed algorithms are evaluated in terms of scheduling latency, the number of scheduled tasks, and time complexity. The simulation results show that the performance of rule based scheduler is seriously degraded in overload situation. However, SA based scheduler and Hybrid scheduler have graceful performance degradation in overload situation. Compared with rule based scheduler, SA based scheduler and Hybrid scheduler can schedule many more tasks on time for the same operation duration in the overload situation. Even though their time complex is relatively high, it can be applied to real applications if the parameters are properly controlled. Especially, Hybrid scheduler has an advantage of low time complexity with good performance.