In this paper, online sparse Volterra system identification is proposed. For that purpose, the conventional adaptive projection-based algorithm with weighted l1 balls (APWL1) is revisited for nonlinear system identification, whereby the linear-in-parameters nature of Volterra systems is utilized. Compared with sparsity-aware recursive least squares (RLS) based algorithms, requiring higher computational complexity and showing faster convergence and lower steady-state error due to their long memory in time-invariant cases, the proposed approach yields better tracking capability in time-varying cases due to short-term data dependence in updating the weight. Also, when N is the number of sparse Volterra kernels and q is the number of input vectors involved to update the weight, the proposed algorithm requires O(qN) multiplication complexity and O(Nlog 2N) sorting-operation complexity. Furthermore, sparsity-aware least mean-squares and affine projection based algorithms are also tested.

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.

Vehicles' speed is one of the key factors in vehicle travel efficiency, as speed is related to vehicle travel time, travel safety, fuel consumption, and exhaust gas emissions (e.g., CO2 emissions). Therefore, to improve the travel efficiency, a recommended speed calculation scheme is proposed to assist driving in Vehicle Ad hoc networks (VANETs) circumstances. In the proposed scheme, vehicles' current speed and space headway are obtained by Vehicle-to-Roadside unit (V2R) communication and Vehicle-to-Vehicle (V2V) communication. Based on the vehicles' current speed and adjacent vehicles' space headway, a recommended speed is calculated by on-board units installed in the vehicles, and then this recommended speed is provided to drivers. The drivers can change their speed to the recommended speed. At the recommended speed, vehicle travel efficiency can be improved: vehicles can arrive at destinations in a shorter travel time with fewer stop times, lower fuel consumption, and less CO2 emission. In particular, when approaching intersections, vehicles can pass through the intersections with less red light waiting time and a higher non-stop passing rate.

In this paper, we propose a novel multi-frame image denoising technique, which achieves the minimum variance of noise. Zero-mean and unknown variance white noise with an arbitrary distribution is considered in this paper. The proposed method consists of two parts. The first one is the estimation of the variance of noise for each image by considering the differences of all pairs of images. The second one is an actual denoising process in which the convex combination of all images with weight coefficients determined by the estimated variances is constructed. We also give an efficient algorithm by which we can obtain the same result by successive convex combinations. The efficacy of the proposed method is confirmed by computer simulations.

For quantized control, one of the powerful approaches is to use a dynamic quantizer, which has internal memories for signal quantization, with a conventional controller in the feedback control loop. The design of dynamic quantizers has become a major topic, and a number of results have been derived so far. In this paper, we extend the authors' recent result on dynamic quantizers, and applied them to a more general class of nonlinear systems, called the nonaffine nonlinear systems. Based on the performance index representing the degradation caused by the signal quantization, we propose practical dynamic quantizers, which include the authors' former result as a special case. Moreover, we provide theoretical results on the performance and on the stability of the resulting quantized systems.

Serial RapidIO (SRIO) is a high-performance interconnection standard for embedded systems. Cyclic Redundancy Check (CRC) provides protection for packet transmissions and impacts the device performances. In this paper, two CRC calculation strategies, based on adjustable slicing parallelization and simplified calculators, are proposed. In the first scheme, the temporary CRC result of the previous cycle (CPre) is considered as a dependent input for the new cycle and is combined with a specific segment of packet data before slicing parallelization. In the second scheme, which can reach a higher maximum working frequency, CPre is considered as an independent input and is separated from the calculation of packet data for further parallelization. Performance comparisons based on ASIC and FPGA implementations are demonstrated to show their effectiveness. Compared with the reference designs, more than 34.8% and 13.9% of average power can be improved by the two proposed schemes at 156.25MHz in 130nm technology, respectively.

In this paper, we propose a use of the group sparsity in adaptive learning of second-order Volterra filters for the nonlinear acoustic echo cancellation problem. The group sparsity indicates sparsity across the groups, i.e., a vector is separated into some groups, and most of groups only contain approximately zero-valued entries. First, we provide a theoretical evidence that the second-order Volterra systems tend to have the group sparsity under natural assumptions. Next, we propose an algorithm by applying the adaptive proximal forward-backward splitting method to a carefully designed cost function to exploit the group sparsity effectively. The designed cost function is the sum of the weighted group l1 norm which promotes the group sparsity and a weighted sum of squared distances to data-fidelity sets used in adaptive filtering algorithms. Finally, Numerical examples show that the proposed method outperforms a sparsity-aware algorithm in both the system-mismatch and the echo return loss enhancement.

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.

Self-resonant helical antenna and capacitor-loaded helical antenna of the same dimension for coupled-resonant wireless power transfer is discussed. At first, fundamental difference of the self-resonant and the capacitor-loaded antenna is demonstrated by calculating electric- and magnetic-coupling coefficient. Next, performance of the helical antennas are discussed from viewpoints of 1) transmission efficiency, 2) undesired emission, 3) near-field leakage, 4) effect of human body and 5) effect of conductivity. We have found that the self-resonant helical antenna has an advantage in low transmission loss due to a conductivity of wire. On the other hand, the capacitor-loaded antenna has an advantage in low emission, long transfer distance, and low influence of resonant frequency from human body. This is because both electric-field coupling and magnetic-field coupling are dominant for the self-resonant antenna while only magnetic-field coupling is dominant in the capacitor-loaded antenna.

This paper describes a robust three-dimensional (3D) surface reconstruction method that can automatically eliminate shadowing errors. For modeling shadowing effect, a new shadowing compensation model based on the angle distribution of backscattered electrons is introduced. Further, it is modified with respect to some practical factors. Moreover, the proposed iterative shadowing compensation method, which performs commutatively between the compensation of image intensities and the modification of the corresponding 3D surface, can effectively provide both an accurate 3D surface and compensated shadowless images after convergence.

Automated or semi-automated annotation is a practical solution for large-scale corpus construction. However, the special characteristics of Thai language, such as lack of word-boundary and sentence-boundary markers, trigger several issues in automatic corpus annotation. This paper presents a multi-stage annotation framework, containing two stages of chunking and three stages of tagging. The two chunking stages are pattern matching-based named entity (NE) extraction and dictionary-based word segmentation while the three succeeding tagging stages are dictionary-, pattern- and statist09812490981249ical-based tagging. Applying heuristics of ambiguity priority, NE extraction is performed first on an original text using a set of patterns, in the order of pattern ambiguity. Next, the remaining text is segmented into words with a dictionary. The obtained chunks are then tagged with types of named entities or parts-of-speech (PoS) using dictionaries, patterns and statistics. Focusing on the reduction of human intervention in corpus construction, our experimental results show that the dictionary-based tagging process can assign unique tags to 64.92% of the words, with the remaining of 24.14% unknown words and 10.94% ambiguously tagged words. Later, the pattern-based tagging can reduce unknown words to only 13.34% while the statistical-based tagging can solve the ambiguously tagged words to only 3.01%.

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.

A joint superimposed sequence design, known as SuperImposed sequence for PAPR Reduction, or SIPR, using per-tone affine precoding technique is proposed to jointly estimate MIMO-OFDM channels and reduce the peak-to-average power ratio (PAPR) for MIMO-OFDM systems. The proposed technique optimizes the trade-off between BER, MSE of the channel estimate, and PAPR reduction performance. Moreover, it does not require side information to be transmitted for the removal of the sequence at the receiver, and the transmit redundancy can be as small as 1 symbol/subcarrier. The superimposed sequence is designed by solving a convex quadratically constrained quadratic programming problem and has a computational complexity comparable to previous technique using linear programming. It is shown that SIPR can be regarded as a generalization of the popular tone reservation (TR) technique, and thus, is able to outperform TR in terms PAPR reduction performance, with less transmit overhead. Simulation results and transmit redundancy analysis of SIPR and TR are shown to illustrate the efficacy of the proposed scheme.

The extensive study and design of Body Area Networks (BANs) and development of related applications have been an object of interest during the last few years. Indeed, the majority of applications have been developed to operate at frequencies up to X band. However nowadays, a new growing attention is being focused on moving the study of BANs to higher frequencies such as those in V andW bands. The characterization of the on-body propagation channel is therefore essential for the design of reliable mm-wave BAN systems. However the classical methods (FDTD, MoM, FEM) commonly used at lower frequencies are not computationally efficient at mm-wave due to the large amount of mesh elements needed to discretize an electrically large geometry such as the human body. To overcome this issue, a ray tracing technique, generally used for characterizing indoor propagation, has been used to analyze a specific channel: chest-to-belt link. The reliability of this high frequency method has been investigated in this paper considering three different test cases. Moreover, a comparison of simulations and measurements, both performed on a body centric scenario at 94GHz, is also presented as well.

With the approval of IEEE 1901 standard for power line communications (PLC) and the recent Internet-enable home appliances like the IPTV having access to a content-on-demand service through the Internet as AcTVila in Japan, there is no doubt that PLC has taken a great step forward to emerge as the preeminent in-home-network technology. However, existing schemes developed so far have not considered the PLC network connected to an unstable Internet environment (i.e. more realistic situation). In this paper, we investigate the communication performance from the end-user's perspective in networks with large and variable round-trip time (RTT) and with the existence of cross-traffic. Then, we address the problem of unfair bandwidth allocation when multiple and different types of flows coexist and propose a TCP rate control considering the difference in terms of end-to-end delay to solve it. We validate our methodology through simulations, and show that it effectively deals with the throughput unfairness problem under critical communication environment, where multiple flows with different RTTs share the PLC and cross-traffic exists on the path of the Internet.

Near range microwave imaging systems have broad application prospects in the field of concealed weapon detection, biomedical imaging, nondestructive testing, etc. In this paper, the technique of optimized sparse antenna array is applied to near range microwave imaging, which can greatly reduce the complexity of imaging systems. In detail, the paper establishes three-dimensional sparse array imaging geometry and corresponding echo model, where the imaging geometry is formed by arranging optimized sparse antenna array in elevation, scanning in azimuth and transmitting broadband signals in range direction; and by analyzing the characteristics of near range imaging, that is, the maximum interval of transmitting and receiving elements is limited by the range from imaging system to targets, we propose the idea of piecewise sparse line array; secondly, by analyzing the convolution principle, we develop a method of arranging piecewise sparse array which can generate the same distribution of equivalent phase centers as filled antenna array; then, the paper deduces corresponding imaging algorithm; finally, the imaging geometry and corresponding algorithm proposed in this paper are investigated and verified via numerical simulations and near range imaging experiments.

In this letter, we use the saliency maps obtained by several bottom-up methods to learn a model to generate a bottom-up saliency map. In order to consider top-down image semantics, we use the high-level features of objectness and background probability to learn a top-down saliency map. The bottom-up map and top-down map are combined through a two-layer structure. Quantitative experiments demonstrate that the proposed method and features are effective to predict human fixation.

This paper proposes the antenna arrangement for 2×2 MIMO (Multiple-Input Multiple-Output) sensor and evaluates the detection performance based on raytracing simulation. In this arrangement, the transmitting and receiving antennas are placed closely. Two types of the arrangement are considered. In the first method, all of the transmitting and receiving antennas are located closely. In the second method, two sets of the antennas are placed separately, and each set has one transmitting and one receiving antennas. The numerical analysis of the indoor propagation based on the raytracing method is carried out. The path distribution and intrusion detection performance with the various antenna arrangements are evaluated for the human positions all over the room. The numerical analysis results show that the proposed antenna arrangements achieve the compact configuration of the sensor antenna system as well as high detection performance.

In terms of the transmission-line theory, a general synthesis of a new class of optimum Chebyshev-type ultra-wideband bandpass (UWB) filter prototype composed of multistage stepped-impedance resonators (SIRs) and two short-circuited shunt stubs positioned at input- and output- ports is presented. By the comparison of the real and theoretical transfer functions, the design/characteristic equations are obtained for the design of the proposed filter prototype rather than the traditional design tables. The explicit expressions of one-stage and two-stage filters are then derived and reported. Accordingly, bandpass filters with an arbitrary FBW (Fractional Bandwidth) and passband ripple can be easily designed by solving the design equations. As an example, a 10-degree Chebyshev distributed filter (two-stage filter) with an FBW of 110% is synthesized to meet FCC's outdoor mask. The synthesized circuit model are confirmed by a commercial circuit simulator and then optimized by an EM simulator, fabricated in microstrip line and characterized by the network analyzer. The good agreements between the measured and predicted frequency responses validate the effectiveness of newly proposed filter prototype and the corresponding synthesis technique. In addition, the designed filter exhibits good characteristics of comparatively low insertion loss, quite sharp skirt, very flat group delay and good stopband (especially in lower one) as well. It should be also highlighted that, compared with the conventional filters composed merely of parallel-coupled SIRs or shunt short-circuit-stubs, the new prototype can reduce the overall length of the filter by more than 3/4λg. Moreover, in terms of the presented design technique, the proposed filter prototype can be also used to easily realize the UWB filters with an FBW even greater than 110%.