This letter describes a speech enhancement algorithm for stereo signals corrupted by diffuse noise. It estimates the noise signal and also a beamformed target signal based on blind target signal cancelation derived from sparsity minimization. Enhanced target speech is obtained by Wiener filtering using both the signals. Experimental results demonstrate the effectiveness of the proposed method.

Reversible data hiding is a technique in which hidden data are embedded in host data such that the consistency of the host is perfectly preserved and its data are restored during extraction of the hidden data. In this paper, a linear prediction technique for reversible data hiding of audio waveforms is improved. The proposed variable expansion method is able to control the payload size through varying the expansion factor. The proposed technique is combined with the prediction error expansion method. Reversible embedding, perfect payload detection, and perfect recovery of the host signal are achieved for a framed audio signal. A smaller expansion factor results in a smaller payload size and less degradation in the stego audio quality. Computer simulations reveal that embedding a random-bit payload of less than 0.4 bits per sample into CD-format music signals provide stego audio with acceptable objective quality. The method is also applied to G.711 µ-law-coded speech signals. Computer simulations reveal that embedding a random-bit payload of less than 0.1 bits per sample into speech signals provide stego speech with good objective quality.

The researches on model-based testing mainly focus on the models with single component, such as FSM and EFSM. For the network protocols which have multiple components communicating with messages, CFSM is a widely accepted solution. But in some network protocols, parallel and data-shared components maybe exist in the same network entity. It is infeasible to precisely specify such protocol by existing models. In this paper we present a new model, Parallel Parameterized Extended Finite State Machine (PaP-EFSM). A protocol system can be modeled with a group of PaP-EFSMs. The PaP-EFSMs work in parallel and they can read external variables form each other. We present a 2-stage test generation approach for our new models. Firstly, we generate test sequences for internal variables of each machine. They may be non-executable due to external variables. Secondly, we process the external variables. We make the sequences for internal variables executable and generate more test sequences for external variables. For validation, we apply this method to the conformance testing of real-life protocols. The devices from different vendors are tested and implementation faults are exposed.

Reduced-reference (RR) image quality assessment (IQA) algorithm aims to automatically evaluate the distorted image quality with partial reference data. The goal of RR IQA metric is to achieve higher quality prediction accuracy using less reference information. In this paper, we introduce a new RR IQA metric by quantifying the difference of discrete cosine transform (DCT) entropy features between the reference and distorted images. Neurophysiological evidences indicate that the human visual system presents different sensitivities to different frequency bands. Moreover, distortions on different bands result in individual quality degradations. Therefore, we suggest to calculate the information degradation on each band separately for quality assessment. The information degradations are firstly measured by the entropy difference of reorganized DCT coefficients. Then, the entropy differences on all bands are pooled to obtain the quality score. Experimental results on LIVE, CSIQ, TID2008, Toyama and IVC databases show that the proposed method performs highly consistent with human perception with limited reference data (8 values).

A terahertz-wave communication system directly connected to an optical fiber network is promising for application to future mobile backhaul and fronthaul links. The possible broad bandwidth in the terahertz band is useful for high-speed signal transmission as well as radio-space encapsulation to the high-frequency carrier. In both cases, the low-latency feature becomes important to enhance the throughput in mobile communication and is realized by waveform transport technology without any digital-signal-processing-based media conversion. A highly precise optical frequency comb signal generated by optical modulation and the vector signal demodulation technology adopted from advanced optical fiber communication technologies help perform modulation and demodulation with impairment compensation at just the edges of the link. Terahertz wave, radio over fiber, waveform transport, coherent detection, multilevel modulation, radio on radio.

A method for measuring the magnetic field strength for human exposure assessment closer than 20cm to wireless power transfer (WPT) systems for information household appliances is investigated based on numerical simulations and measurements at 100kHz and 6.78MHz. Four types of magnetic sources are considered: a simple 1-turn coil and three types of coils simulating actual WPT systems. A magnetic sensor whose cross sectional area is 100cm2 as prescribed in International Electrotechnical Commission 62233 is used. Simulation results show that the magnetic field strength detected by the magnetic sensor is affected by its placement angle. The maximum coefficient of variation (CV) is 27.2% when the magnetic source and the sensor are in contact. The reason for this deviation is attributable to the localization of the magnetic field distribution around the magnetic source. The coupling effect between the magnetic source and the sensor is negligible. Therefore, the sensor placement angle is an essential factor in magnetic field measurements. The CV due to the sensor placement angle is reduced from 21% to 4% if the area of the sensor coil is reduced from 100 to 0.75cm2 at 6.78MHz. However, the sensitivity of the sensor coil is decreased by 42.5dB. If measurement uncertainty that considers the deviation in the magnetic field strength due to the sensor placement angle is large, the measured magnetic field strength should be corrected by the uncertainty. If the magnetic field distribution around the magnetic source is known, conservative exposure assessments can be achieved by placing the magnetic sensor in locations at which the spatial averaged magnetic field strengths perpendicular to the magnetic sensor coils become maximum.

This letter investigates the circularity of fractional Fourier transform (FRFT) coefficients containing noise only, and proves that all coefficients coming from white Gaussian noise are circular via the discrete FRFT. In order to use the spectrum kurtosis (SK) as a Gaussian test to check if linear frequency modulation (LFM) signals are present in a set of FRFT points, the effect of the noncircularity of Gaussian variables upon the SK of FRFT coefficients is studied. The SK of the α th-order FRFT coefficients for LFM signals embedded in a white Gaussian noise is also derived in this letter. Finally the signal detection algorithm based on FRFT and SK is proposed. The effectiveness and robustness of this algorithm are evaluated via simulations under lower SNR and weaker components.

Superconducting single-flux-quantum (SFQ) device is an emerging device which can realize digital circuits with high switching speed and low power consumption. In SFQ digital circuits, voltage pulses are used for carrier of information, and the representation of logic values is different from that of CMOS circuits. Design methods exclusive to SFQ circuits have been developed. In this paper, we present timing analysis and functional verification methods for SFQ circuits based on new timing model which we call delay-based time frame model. Assuming that possible pulse arrival is periodic, the model defines comprehensive time frames and representation of logic values. In static timing analysis, expected pulse arrival time is checked based on the model, and the order among pulse arrival times is calculated for each logic gate. In functional verification, the circuit behavior is abstracted in a form similar to a synchronous sequential circuit using the order of pulse arrival times, and then the behavior is verified using formal verification tools. Using our proposed methods, we can verify the functional behavior of SFQ circuits with complex clocking scheme, which appear often in practical design but cannot be dealt with in existing verification method. Experimental results show that our method can be applied to practical designs.

An earthquake is a destructive natural disaster, which cannot be predicted accurately and causes devastating damage and losses. In fact, many of the damages can be prevented if people know what to do during and after earthquakes. Earthquake education is the most important method to raise public awareness and mitigate the damage caused by earthquakes. Generally, earthquake education consists of conducting traditional earthquake drills in schools or communities and experiencing an earthquake through the use of an earthquake simulator. However, these approaches are unrealistic or expensive to apply, especially in underdeveloped areas where earthquakes occur frequently. In this paper, an earthquake drill simulation system based on virtual reality (VR) technology is proposed. A User is immersed in a 3D virtual earthquake environment through a head mounted display and is able to control the avatar in a virtual scene via Kinect to respond to the simulated earthquake environment generated by SIGVerse, a simulation platform. It is a cost effective solution and is easy to deploy. The design and implementation of this VR system is proposed and a dormitory earthquake simulation is conducted. Results show that powerful earthquakes can be simulated successfully and the VR technology can be applied in the earthquake drills.

The multiterminal hypothesis testing problem with zero-rate constraint is considered. For this problem, an upper bound on the optimal error exponent is given by Shalaby and Papamarcou, provided that the positivity condition holds. Our contribution is to prove that Shalaby and Papamarcou's upper bound is valid under a weaker condition: (i) two remote observations have a common random variable in the sense of Gácks and Körner, and (ii) when the value of the common random variable is fixed, the conditional distribution of remaining random variables satisfies the positivity condition. Moreover, a generalization of the main result is also given.

To analyze the structure of a set of high-dimensional perfect sequences over a composition algebra over R, we developed the theory of Fourier transforms of the set of such sequences. We define the discrete cosine transform and the discrete sine transform, and we show that there exists a relationship between these transforms and a convolution of sequences. By applying this property to a set of perfect sequences, we obtain a parameterization theorem. Using this theorem, we show the equivalence between the left perfectness and right perfectness of sequences. For sequences of real numbers, we obtain the parameterization without restrictions on the parameters.

The RO (Ring-Oscillator)-based sensor is one of easily-implementable variation sensors, but for decomposing the observed variability into multiple unique device-parameter variations, a large number of ROs with different structures and sensitivities to device-parameters is required. This paper proposes an area efficient device parameter estimation method with sensitivity-configurable ring oscillator (RO). This sensitivity-configurable RO has a number of configurations and the proposed method exploits this property for reducing sensor area and/or improving estimation accuracy. The proposed method selects multiple sets of sensitivity configurations, obtains multiple estimates and computes the average of them for accuracy improvement exploiting an averaging effect. Experimental results with a 32-nm predictive technology model show that the proposed averaging with multiple estimates can reduce the estimation error by 49% or reduce the sensor area by 75% while keeping the accuracy. Compared to previous work with iterative estimation, 23% accuracy improvement is achieved.

In this paper, the repeatable hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. The authors' had previously proposed a hybrid parallel algorithm for inverse matrix computation. It is reasonably fast for a one time computation of an inverse matrix, but it is hard to apply this algorithm repeatedly for consecutive computations since the relocation of the large matrix is required at the beginning of each iterations. In order to eliminate the relocation of the large input matrix which is the output of the inverse matrix computation from the previous time step, the computation algorithm has been redesigned so that the required portion of the input matrix becomes the same as the output portion of the previously computed matrix in each node. This makes it possible to repeatedly and efficiently apply the SMW formula to compute inverse matrix in a time-series simulation.

As the use of information technology is rapidly expanding, the power consumption of IT equipment is becoming an important social issue. As such, the power supply of IT equipment must provide various power saving measures through advanced features. A digitally controlled power supply is attractive for satisfying this requirement due to its flexibility and advanced management functionality. However, a digitally controlled power supply has issues with its transient response performance because the conversion time of the analog-digital converter and the time required for digital processing in the digital controller adversely affect the dynamic characteristics. The present paper introduces a new approach that can improve the transient response performance of the digital point-of-load (POL) power supplies of computer processors. The resulting power systems use feed-forward transient control, in addition to the general voltage regulation feedback control loop, to improve their dynamic characteristics. On the feed-forward control path, the processor workload information is supplied to the power supply controller from the processor. The power supply controller uses the workload information to predict the power load change and generates an auxiliary control to improve the transient response performance. As the processor workload information, the processor-integrated performance counter values are sent to the power supply controller via a hardware interface. The processor power consumption prediction equation is modeled using the moving average model, which uses performance counter values of several past steps. The prediction equation parameters are defined by multiple regression analysis using the measured CPU power consumption data and experimentally obtained performance counter information. The analysis reveals that the optimum parameters change with time during transient periods. The modeled equation well explains the processor power load change. The measured CPU power consumption profile is confirmed to be accurately replicated by the prediction for a period of 200ns. Using the power load change prediction model, circuit simulations of the feed-forward transient control are conducted. It is validated that the proposed approach improves power supply transient response under some practical server workloads.

In the study of the capacity problem for multiple access channels (MACs), a lower bound on the error probability obtained by Han plays a crucial role in the converse parts of several kinds of channel coding theorems in the information-spectrum framework. Recently, Yagi and Oohama showed a tighter bound than the Han bound by means of Polyanskiy's converse. In this paper, we give a new bound which generalizes and strengthens the Yagi-Oohama bound, and demonstrate that the bound plays a fundamental role in deriving extensions of several known bounds. In particular, the Yagi-Oohama bound is generalized to two different directions; i.e, to general input distributions and to general encoders. In addition we extend these bounds to the quantum MACs and apply them to the converse problems for several information-spectrum settings.

The authors proposed an algorithm for calculation of new lower bound (rank bounded distance) using the discrete Fourier transform in 2010. Afterward, we considered some algorithms to improve the original algorithm with moving the row or column. In this paper, we discuss the calculation method of the rank bounded distance by conjugate elements for cyclic codes.

The dramatic growth in wireless data traffic has triggered the investigation of fifth generation (5G) wireless communication systems. Small cells will play a very important role in 5G to meet the 5G requirements in spectral efficiency, energy savings, etc. In this paper, we investigate low complexity millimeter-wave communication systems with uniform circular arrays (UCAs) in line-of-sight (LOS) multiple-input multiple-output (MIMO) channels, which are used in fixed wireless access such as small cell wireless backhaul for 5G. First, we demonstrate that the MIMO channel matrices for UCAs in LOS-MIMO channels are circulant matrices. Next, we provide a detailed derivation of the unified optimal antenna placement which makes MIMO channel matrices orthogonal for 3×3 and 4×4 UCAs in LOS channels. We also derive simple analytical expressions of eigenvalues and capacity as a function of array design (link range and array diameters) for the concerned systems. Finally, based on the properties of circulant matrices, we propose a high performance low complexity LOS-MIMO precoding system that combines forward error correction (FEC) codes and spatial interleaver with the fixed IDFT precoding matrix. The proposed precoding system for UCAs does not require the channel knowledge for estimating the precoding matrix at the transmitter under the LOS condition, since the channel matrices are circulant ones for UCAs. Simulation results show that the proposed low complexity system is robust to various link ranges and can attain excellent performance in strong LOS environments and channel estimation errors.

This letter proposes an image fusion method which adopts a union of multiple directional lapped orthogonal transforms (DirLOTs). DirLOTs are used to generate symmetric orthogonal discrete wavelet transforms and then to construct a union of unitary transforms as a redundant dictionary with a multiple directional property. The multiple DirLOTs can overcome a disadvantage of separable wavelets to represent images which contain slant textures and edges. We analyse the characteristic of local luminance contrast, and propose a fusion rule based on interscale relation of wavelet coefficients. Relying on the above, a novel image fusion method is proposed. Some experimental results show that the proposed method is able to significantly improve the fusion performance from those with the conventional discrete wavelet transforms.

A Bayer-like White-RGB (W-RGB) color filter array (CFA) was invented for overcoming the weaknesses of commonly used RGB based Bayer CFA. In order to reproduce full-color images from the Bayer-like W-RGB CFA, a demosaicing or a CFA interpolation process which estimates missing color channels of raw mosaiced images from CFA is an essential process for single sensor digital cameras having CFA. In the case of Bayer CFA, numerous demosaicing methods which have remarkable performance were already proposed. In order to take advantage of both remarkable performance of demosaicing method for Bayer CFA and the characteristic of high-sensitive Bayer-like W-RGB CFA, a new method of transforming Bayer-like W-RGB to Bayer pattern is required. Therefore, in this letter, we present a new method of transforming Bayer-like W-RGB pattern to Bayer pattern. The proposed method mainly uses the color difference assumption between different channels which can be applied to practical consumer digital cameras.

New payment technologies are coming that will raise user convenience. To support automatic hands-free payment, merchant devices will collect customer's information from the cloud of payment service providers or customer's smart phones, which should be removed after the transaction. Using Jaccard containment, we propose a proactive security approach of cleaning personal data at merchant-side point-of-sale terminals. We also propose a sampling method to reduce communication overhead by several orders of magnitude.