As a consequence of recent developments in communications, the parameters of communication signals, such as the modulation parameter values, are becoming unstable because of time-varying SNR under electromagnetic conditions. In general, it is difficult to classify target signals that have time-varying parameters using traditional signal recognition methods. To overcome this problem, this study proposes a novel recognition method that works well even for such time-dependent communication signals. This method is mainly composed of feature extraction and classification processes. In the feature extraction stage, we adopt Shannon entropy and index entropy to obtain the stable features of modulated signals. In the classification stage, the interval gray relation theory is employed as suitable for signals with time-varying parameter spaces. The advantage of our method is that it can deal with time-varying SNR situations, which cannot be handled by existing methods. The results from numerical simulation show that the proposed feature extraction algorithm, based on entropy characteristics in time-varying SNR situations,offers accurate clustering performance, and the classifier, based on interval gray relation theory, can achieve a recognition rate of up to 82.9%, even when the SNR varies from -10 to -6 dB.

This paper introduces our developed noise robust speech communication techniques and describes its implementation to a smart info-media system, i.e., a small robot. Our designed speech communication system consists of automatic speech detection, recognition, and rejection. By using automatic speech detection and recognition, an observed speech waveform can be recognized without a manual trigger. In addition, using speech rejection, this system only accepts registered speech phrases and rejects any other words. In other words, although an arbitrary input speech waveform can be fed into this system and recognized, the system responds only to the registered speech phrases. The developed noise robust speech processing can reduce various noises in many environments. In addition to the design of noise robust speech recognition, the LSI design of this system has been introduced. By using the design of speech recognition application specific IC (ASIC), we can simultaneously realize low power consumption and real-time processing. This paper describes the LSI architecture of this system and its performances in some field experiments. In terms of current speech recognition accuracy, the system can realize 85-99% under 0-20dB SNR and echo environments.

This paper proposes novel robust speech F0 estimation using Summation Residual Harmonics (SRH) based on TV-CAR (Time-Varying Complex AR) analysis. The SRH-based F0 estimation was proposed by A. Alwan, in which the criterion is calculated from LP residual signals. The criterion is summation of residual spectrum value for harmonics. In this paper, we propose SRH-based F0 estimation based on the TV-CAR analysis, in which the criterion is calculated from the complex AR residual. Since complex AR residual provides higher resolution of spectrum, it can be considered that the criterion is effective for F0 estimation. The experimental results demonstrate that the proposed method performs better than conventional methods; weighted auto-correlation and YIN.

LTE-Advanced supports asymmetric carrier aggregation (CA) to achieve flexible bandwidth allocation by applying different numbers of component carriers (CCs) between the downlink and uplink. This paper experimentally clarifies the achievable downlink throughput performance when uplink control information (UCI) feedback mechanism using the physical uplink shared channel (PUSCH), which enables minimization of the UCI overhead while maintaining the required reception quality, is applied in asymmetric CA. The laboratory experimental results show that the stable reception quality control of the channel quality information (CQI) with the target block error rate (BLER) of 10-1 to 10-2 is achieved irrespective of the average received signal-to-noise power ratio (SNR) when the control offset parameter of approximately 1.25 is used. We also show that the achievable downlink throughput when the CQI error is considered is almost the same as that in no CQI error case. Furthermore, based on the experimental results in a real field environment, a suburban area of Yokosuka city in Japan, we confirm stable adaptive modulation and coding (AMC) operation including target BLER control of the CQI on the PUSCH in asymmetric CA. The field experimental results also show that when CA with 5 CCs (90-MHz bandwidth) and 2-by-2 rank-2 multiple-output multiple-input (MIMO) multiplexing are employed in the downlink, the peak throughput of approximately 640Mbps is achieved even considering the CQI error.

We designed multilayer wavelength-selective reflector films by stacking thin-films of transparent polymer. The optimum structure of the multilayer is determined using a combination of characteristic matrix method and a version of genetic algorithm. Such multilayer films can be used in LCD devices to enhance the color saturation of the display.

In this paper, we introduce a new multi-operator pico eNodeB (eNB) concept for cellular networks. It is expected that mobile data offloading will be performed effectively after installing the pico eNBs in cellular networks, owing to the rapid increase in mobile traffic. However, when several different operators independently install the pico eNBs, high costs and large amounts of space will be required for the installation. In addition, when several different operators accommodate their own user equipments (UEs) in the pico eNBs, not enough UEs can be accommodated. This is because the UEs are not evenly distributed in the coverage area of the pico eNBs. In this paper, the accommodation of the UEs of different operators in co-sited pico eNB is discussed as one of the solutions to these problems. For the accommodation of the UEs of different operators, wireless resources should be allocated to them. However, when each operator independently controls his wireless resources, the operator is not provided with an incentive to accommodate the UEs of the other operators in his pico eNBs. For this reason, an appropriate rule for appropriate allocation of the wireless resources to the UEs of different operators should be established. In this paper, by using the concepts of game theory and mechanism design, a resource allocation rule where each operator is provided with an incentive to allocate the wireless resources to the UEs of different operators is proposed. With the proposed rule, each operator is not required to disclose the control information like link quality and the number of UEs to the other operators. Furthermore, the results of a throughput performance evaluation confirm that the proposed scheme improves the total throughput as compared with individual resource allocation.

This paper deals with the problem of underdetermined blind source separation (BSS) where the number of sources is unknown. We propose a BSS approach that simultaneously estimates the number of sources, separates the sources based on the sparseness of speech, estimates the direction of arrival of each source, and performs permutation alignment. We confirmed experimentally that reasonably good separation was obtained with the present method without specifying the number of sources.

This paper presents a method of synthesizing covariance matrix elements of array input signal for high resolution 2-D Direction-Of-Arrival (DOA) estimation via antenna (sensor) switching. Antenna array generally has the same number of array elements and receiver modules which often leads large receiver hardware cost. Two of the authors have already studied a way of antenna switching to reduce receiver cost, but it can be applied only for periodic incident signals like sinusoid. In this paper, we propose two simple methods of DOA estimation from sparse data by synthesizing covariance matrix elements of array input signal via antenna switching, which can also be applied to DOA estimation of antiperiodic incident signals. Performance of the proposed approach is evaluated in detail through some computer simulation.

We propose a maximum likelihood estimation approach for the recovery of continuously-defined sparse signals from noisy measurements, in particular periodic sequences of Diracs, derivatives of Diracs and piecewise polynomials. The conventional approach for this problem is based on least-squares (a.k.a. annihilating filter method) and Cadzow denoising. It requires more measurements than the number of unknown parameters and mistakenly splits the derivatives of Diracs into several Diracs at different positions. Moreover, Cadzow denoising does not guarantee any optimality. The proposed approach based on maximum likelihood estimation solves all of these problems. Since the corresponding log-likelihood function is non-convex, we exploit the stochastic method called particle swarm optimization (PSO) to find the global solution. Simulation results confirm the effectiveness of the proposed approach, for a reasonable computational cost.

This paper studies the static mapping of multiple applications on embedded many-core SoCs. The mapping techniques proposed in this paper take into account both inter-application and intra-application parallelism in order to fully utilize the potential parallelism of the many-core architecture. Two approaches are proposed for static mapping: one approach is based on integer linear programming and the other is based on a greedy algorithm. Experiments show the effectiveness of the proposed techniques.

This paper proposes a method for testing delay faults using a boundary scan circuit in which a time-to-digital converter (TDC) is embedded. The incoming transitions from the other cores or chips are captured at the boundary scan circuit. The TDC circuit is modified to set the initial value for a delay line through which the transition is propagated. The condition for measuring timing slacks of two or more paths is also investigated since the overlap of the signals may occur in the delay line of the TDC in our boundary scan circuit. An experimental IC with the TDC and boundary scan is fabricated and is measured to estimate the delay of some paths measured by the TDC embedded in boundary scan cells. The simulation results for a benchmark circuit with the boundary scan circuit are also shown for the case that timing slacks of multiple paths can be observed even if the signals overlap in the TDC.

In this paper, a method is introduced that can detect the number of incident signals (NIS) even there are fewer antennas than NIS. Previous works on NIS detection methods assumed that the number of antennas always exceeded NIS. In the DOA estimation field, the DOA estimation is possible, even if NIS exceeds the number of antennas, by extending the degrees of freedom of array (DOFA) using a modified array configuration, such as a nested array (NA). The information of NIS is required in advance to accurately estimate DOA, however, it has not been investigated deeply when NIS is larger than the number of antennas. In this paper, a NIS detection method based on the DOFA extending process using NA is proposed. One of the important issues in NIS detection is the detection metric. As one of the simple metrics, the ratio of adjacent eigenvalues (RAE) has been used. However, the direct application of RAE may not achieve adequate NIS detection performance. Therefore, we propose a metric based on the modified ratio of adjacent eigenvalues (MRAE) avoids the issue of RAE. Numerical results show that the metric based on MRAE can achieve proper NIS detection performance even if NIS is larger than the number of antennas.

We propose an asynchronous datapath for the low-density parity-check decoder to decrease power consumption. Glitches and redundant computations are decreased by the asynchronous design. Taking advantage of the statistical characteristics of the input data, we develop novel key arithmetic elements in the datapath to reduce redundant computations. Two other types of datapaths, including normal synchronous design and clock-gating design, are implemented for comparisons with the proposed design. The three designs use similar architectures and realize the same function by using the 0.18µm process of the Semiconductor Manufacturing International Corporation. Post-layout result shows that the proposed asynchronous design exhibits the lowest power consumption. The proposed asynchronous design saves 48.7% and 21.9% more power than the normal synchronous and clock-gating designs, respectively. The performance of the proposed datapath is slightly worse than the clock-gating design but is better than the synchronous design. The proposed design is approximately 7% larger than the other two designs.

As the LSI process technology advances and the gate size becomes smaller, the signal delay on interconnect becomes a significant factor in the signal path delay. Also, as the size of interconnect structure becomes smaller, the interconnect process variations have become one of the dominant factors which influence the signal delay and thus clock skew. Therefore, controlling the influence of interconnect process variations on clock skew is a crucial issue in the advanced process technologies. In this paper, we propose a method for minimizing clock skew fluctuations caused by interconnect process variations. The proposed method identifies the suitable balance of clock buffer size and wire length in order to minimize the clock skew fluctuations caused by the interconnect process variations. Experimental results on test circuits of 28nm process technology show that the proposed method reduces the clock skew fluctuations by 30-92% compared to the conventional method.

This paper presents a novel data compression method for testing integrated circuits within the framework of pattern run-length coding. The test set is firstly divided into 2n-length patterns where n is a natural number. Then the compatibility of each pattern, which can be an external type, or an internal type, is analyzed. At last, the codeword of each pattern is generated according to its analysis result. Experimental results for large ISCAS89 benchmarks show that the proposed method can obtain a higher compression ratio than existing ones.

As mobile multimedia services expand, user behavior will become more diverse and the control of service quality from the user's perspective will become more important in service design. The quality of the network is one of the critical factors determining mobile service quality. However, this has mainly been evaluated in objective physical terms, such as delay reduction and bandwidth expansion. It is less common to use a human-centered design viewpoint when improving network performance. In this paper, we discuss ways to improve the quality of web services using time-fillers that actively address the human factors to improve the subjective quality of a mobile network. A field experiment was conducted, using a prototype. The results of the field experiment show that time-fillers can significantly decrease user dissatisfaction with waiting, but that this effect is strongly influenced by user preferences concerning content. Based on these results, we discuss the design requirements for effective use of time-fillers.

This paper proposes the physical architecture of an electric power system with multiple homes. The notion of home is a unit of small-scale power system that includes local energy source, energy storage, load, power conversion circuits, and control systems. An entire power system consists of multiple homes that are interconnected via a distribution network and that are connected to the commercial power grid. The interconnection is autonomously achieved with a recently developed technology of grid-connected inverters. A mathematical model of slow dynamics of the power system is also developed in this paper. The developed model enables the evaluation of steady and transient characteristics of power systems.

We have proposed a method of identifying superspreaders by flow sampling and a method of filtering legitimate hosts from the identified superspreaders using a white list. However, the problem of how to optimally set parameters of φ, the measurement period length, m*, the identification threshold of the flow count m within φ, and H*, the identification probability for hosts with m=m*, remained unsolved. These three parameters seriously impact the ability to identify the spread of infection. Our contributions in this work are two-fold: (1) we propose a method of optimally designing these three parameters to satisfy the condition that the ratio of the number of active worm-infected hosts divided by the number of all vulnerable hosts is bound by a given upper-limit during the time T required to develop a patch or an anti-worm vaccine, and (2) the proposed method can optimize the identification accuracy of worm-infected hosts by maximally using a limited amount of memory resource of monitors.

A mixed storage-type design using flip-flops and latches (FF/latch-based design) has advantages on such as area and power compared to single storage-type design (only flip-flops or latches). Considering FF/latch-based design at high-level synthesis is necessary, because resource binding process significantly affects the quality of resulting circuits. One of the fundamental aspects in FF/latch-based design is that different resource binding solutions could lead to the different numbers of latch-replacable registers. Therefore, as a first step, this paper addresses a datapath design problem in which resource binding and selecting storage-types of registers are simultaneously optimized for datapath area minimization (i.e., latch replacement maximization). An efficient algorithm based on the compatibility path decomposition and an integer linear programming-based exact approach are presented. Experiments confirm the effectiveness of the proposed approaches.

The topic of retrieving videos containing a desired person from a dataset just using the content of faces without any help of textual information has many interesting applications like video surveillance, social network, video mining, etc. However, traditional face matching against a huge number of detected faces leads to an unacceptable response time and may also reduce the accuracy due to the large variations in facial expressions, poses, lighting, etc. Therefore, in this paper we propose a novel method to generate discriminative “signatures” for efficiently retrieving the videos containing the same person with a query. In this research, the signature is defined as a compact, discriminative and reduced dimensionality representation, which is generated from a set of high-dimensional feature vectors of an individual. The desired videos are retrieved based on the similarities between the signature of the query and those of individuals in the database. In particular, we make the following contributions. Firstly, we give an algorithm of two directional linear discriminant analysis with maximum correntropy criterion (2DLDA-MCC) as an extension to our recently proposed maximum correntropy criterion based linear discriminant analysis (LDA-MCC). Both algorithms are robust to outliers and noise. Secondly, we present an approach for transferring a set of exemplars to a fixed-length signature using LDA-MCC and 2DLDA-MCC, resulting in two kinds of signatures that are called 1D signature and 2D signature. Finally, a novel video retrieval scheme is given based on the signatures, which has low storage requirement and can achieve a fast search. Evaluations on a large dataset of videos show reliable measurement of similarities by using the proposed signatures to represent the identities generated from videos. Experimental results also demonstrate that the proposed video retrieval scheme has the potential to substantially reduce the response time and slightly increase the mean average precision of retrieval.