This paper presents a spatial division (SD) transmission method based on two-ray fading that dispenses with the high signal processing cost of multiple-input and multiple-output (MIMO) detection and antennas with narrow beamwidth. We show the optimum array geometries as functions of the transmission distance for providing a concrete array design method. Moreover, we clarify achievable channel capacity considering reflection coefficients that depend on the polarization, incident angle, and dielectric constant. When the ground surface is conductive, for two- and three-element arrays, channel capacity is doubled and tripled, respectively, over that of free space propagation. We also clarify the application limit of this method for a dielectric ground by analyzing the channel capacity's dependency on the dielectric constant. With this method, increased channel capacity by SD transmission can be obtained merely by placing antennas of wireless transceiver sets that have only SISO (single-input and single-output) capability in a two-ray propagation environment. By using formulations presented in this paper for the first time and adding discussions on the adoption of polarization multiplexing, we clarify antenna geometries of SD transmission systems using polarization multiplexing for up to six streams.

Hands-free communications between cellular phones must be robust enough to withstand echo-path variation, and highly nonlinear echoes must be suppressed at low cost, when acoustic echo cancellation or suppression is applied to them. This paper proposes a spectrum-selective nonlinear echo suppression (SS-ES) approach as a solution to these issues. SS-ES is characterized by the selection of either a spectrum of the residual signal from an adaptive filter or a spectrum of the sending input signal depending on the amount of linear echo cancellation in an adaptive filter. Compared to conventional methods, the objective evaluation results of the SS-ES approach show an improvement of approximately 0.8-2.2dB, 0.23-2.39dB, and 0.26-0.50 in average echo return loss enhancement (ERLE), average root-mean-square log-spectral distortion (RMS-LSD), and the perceptual evaluation of speech quality (PESQ) value, respectively, under echo-path variation and double-talk conditions.

High efficiency video coding (HEVC) is a video compression standard that outperforms the predecessor H.264/AVC by doubling the compression efficiency. To enhance the intra prediction accuracy, 35 intra prediction modes were used in the prediction units (PUs), with partition sizes ranging from 4 × 4 to 64 × 64 in HEVC. However, the manifold prediction modes dramatically increase the encoding complexity. This paper proposes a fast mode- and depth-decision algorithm based on edge detection and reconfiguration to alleviate the large computational complexity in intra prediction with trivial degradation in accuracy. For mode decision, we propose pixel gradient statistics (PGS) and mode refinement (MR). PGS uses pixel gradient information to assist in selecting the prediction mode after rough mode decision (RMD). MR uses the neighboring mode information to select the best PU mode (BPM). For depth decision, we propose a partition reconfiguration algorithm to replace the original partitioning order with a more reasonable structure, by using the smoothness of the coding unit as a criterion in deciding the prediction depth. Smoothness detection is based on the PGS result. Experiment results show that the proposed method saves about 41.50% of the original processing time with little degradation (BD bitrate increased by 0.66% and BDPSNR decreased by 0.060dB) in the coding gain.

In this paper, we propose demodulators for the Golden and Alamouti codes in amplify-and-forward (AF) cooperative communication with one relay. The proposed demodulators output exact log likelihood ratios (LLRs) with recursion based on the Jacobian logarithm. The cooperative system with the proposed demodulator for the Golden code has the benefit of efficient data transmission, while the system for the Alamouti code has low demodulation complexity. Quantitative analyses of computational complexity of the proposed demodulators are conducted. The transmission performance for various relay location and power settings is evaluated on cooperative orthogonal frequency division multiplexing (OFDM)-based wireless local area network (LAN) systems. In evaluations, the optimal relay location and power settings are found. The cooperative system with the proposed demodulators for the Golden and Alamouti codes offers 1.5 and 1.9 times larger areas where 10.8 and 5.4Mbit/s can be obtained than a non-cooperative (direct) system in a typical office environment, respectively.

We consider an improved control method based on the Stability Transformation Method. Stability Transformation Method detects unknown and unstable periodic orbits of chaotic dynamical systems. Based on the approach to realize the Stability Transformation Method in real systems, we have proposed a control method which can stabilize unknown and unstable periodic orbits embedded in chaotic attractors. However, setting of the control parameters of the control system has remained as unsolved issue. When the dynamics of a target system are unknown, the control parameters have to be set by trial and error. In this paper, we improve the control method with the automatic adjustment function of the control parameters. We show an example of stabilizing unstable periodic orbits of the 3-dimensional hysteresis chaos generator by using the proposed control method. Some results are confirmed by laboratory measurements. The results imply that any unknown and unstable periodic orbits can be stabilized by using the proposed method, if the target chaos system is reduced to 1-dimensional return map.

One of the major applications of contrast-enhanced ultrasound (CEUS) is lesion classification. After contrast agents are administered, it is possible to identify a lesion type from its enhancement pattern. However, CEUS image reading is not easy because there are various types of enhancement patterns even for the same type of lesion, and clear classification criteria have not yet been defined. Some studies have used conventional time intensity curves (TICs), which show the vessel dynamics of a lesion. It is possible to predict lesion type from the TIC parameters, such as the coefficients obtained by curve fitting, peak intensity, flow rate and time to peak. However, these parameters are not always provide sufficient accuracy. In this paper, we prepare 1D Haar-like features which describe intensity changes in a TIC and adopt the Adaboost machine learning technique, which eases understanding of which features are useful. Hyperparameters of weak classifiers, e.g., the step size of a Haar-like filter length and threshold for output of the filter, are optimized by searching for those parameters that give the best accuracy. We evaluate the proposed method using 36 focal splenic lesions in canines 16 of which were benign and 20 malignant. The accuracies were 91.7% (33/36) when inspected by an experienced veterinarian, 75.0% (27/36) by linear discriminant analysis (LDA) using conventional three TIC parameters: time to peak, area under curve and peak intensity, and 91.7% (33/36) using our proposed method. McNemar testing shows the p-value to be less than 0.05 between the proposed method and LDA. This result shows the statistical significance of differences between the proposed method and the conventional TIC analysis method using LDA.

This paper analyzes the transmission performances of visible light communication (VLC) based on unipolar orthogonal frequency division multiplexing (OFDM), which is compatible with intensity modulation and direct detection (IM/DD). Three existing unipolar OFDM schemes, namely DC biased optical OFDM (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), and flip-OFDM are investigated and compared. While these three schemes have been analyzed for indoor optical wireless communication (OWC) subject to the limitation on the transmit optical power, they have not been carefully investigated and compared for VLC when a large transmit power is available due to the illumination requirement, and the signal dynamic range (DR) becomes the main limitation. For the analysis, DR expressions of DCO-OFDM, ACO-OFDM, and flip-OFDM signals are first derived. Then, the bit error rate (BER) expression of each unipolar OFDM scheme is derived in terms of the DR. For data rates in the range of 1-10Mbps, under the system parameters based on typical indoor environments, DCO-OFDM is observed to outperform the other two schemes. This superiority of DCO-OFDM is in contrast with previously reported results that indicate the attractiveness of ACO-OFDM and flip-OFDM over DCO-OFDM when the transmit optical power is the main limitation. Finally, light dimming is considered to identify the illumination level below which DCO-OFDM loses this superiority.

The bilateral filter (BF) is a nonlinear and low-pass filter which can smooth an image while preserving detail structures. However, the filer is time consuming for real-time processing. In this paper, we bring forward a fresh idea that bilateral filtering can be accelerated by a multigrid (MG) scheme. Our method is based on the following two facts. a) The filtering result by a BF with a large kernel size on the original resolution can be approximated by applying a small kernel sized (3×3) version on the lower resolution many times on the premise of visual acceptance. Early work has shown that a BF can be viewed as nonlinear diffusion. The desired filtering result is actually an intermediate status of the diffusion process. b) Iterative linear equation techniques are sufficiently mature to cope with the nonlinear diffusion equation, which can be accelerated by the MG scheme. Experimental results with both simulated data sets and real sets are provided, and the new method is demonstrated to achieve almost twice the speed of the state-of-the-art. Compared with previous efforts for finding a generalized representation to link bilateral filtering and nonlinear diffusion by adaptive filtering, a novel relationship between nonlinear diffusion and bilateral filtering is explored in this study by focusing attention on numerical calculus.

This paper proposes a compact three-mode H-shaped resonator bandpass filter fed by antiparallel coupled input/output lines. To investigate the resonant behavior of the H-shaped resonator, even/odd-mode resonance conditions of the resonator are first derived analytically. The multimode resonances of the H-shaped resonator filter are modeled by a multipath circuit formed with resonance paths. Moreover, a direct source/load coupling path is connected in parallel, of which the value shows a frequency dependency because of the antiparallel coupled feeding lines, thereby generating four transmission zeros (TZs) greater than the number of a theoretical limitation. The H-shaped resonator bandpass filter is synthesized, developed, and tested, showing a third-order passband response with four TZs located near the passband, and a wide stopband property.

This paper shows a method to represent interval functions by using head-tail expressions. The head-tail expressions represent greater-than GT(X:A) functions, less-than LT(X:B) functions, and interval functions IN0(X:A,B) more efficiently than sum-of-products expressions. Let n be the number of bits to represent the largest value in the interval (A,B). This paper proves that a head-tail expression (HT) represents an interval function with at most n words in a ternary content addressable memory (TCAM) realization. It also shows the average numbers of factors to represent interval functions by HTs for up to n=16, which were obtained by a computer simulation. It also conjectures that, for sufficiently large n, the average number of factors to represent n-variable interval functions by HTs is at most 2/3n-5/9. Experimental results also show that, for n≥10, to represent interval functions, HTs require at least 20% fewer factors than MSOPs, on the average.

The goal of dimension reduction is to represent high-dimensional data in a lower-dimensional subspace, while intrinsic properties of the original data are kept as much as possible. An important challenge in unsupervised dimension reduction is the choice of tuning parameters, because no supervised information is available and thus parameter selection tends to be subjective and heuristic. In this paper, we propose an information-theoretic approach to unsupervised dimension reduction that allows objective tuning parameter selection. We employ quadratic mutual information (QMI) as our information measure, which is known to be less sensitive to outliers than ordinary mutual information, and QMI is estimated analytically by a least-squares method in a computationally efficient way. Then, we provide an eigenvector-based efficient implementation for performing unsupervised dimension reduction based on the QMI estimator. The usefulness of the proposed method is demonstrated through experiments.

A coherent combining-based initial ranging scheme is proposed for multiple-input multiple-output and orthogonal frequency division multiple access systems. The proposed algorithm utilizes the correlation properties of the ranging codes to resolve the multipath components, coherently combines the initial ranging signal of resolved path on each receiving antenna to maximize the output signal-to-interference-and-noise ratio, and then collects the power of the multipath signals to detect the states of the ranging codes. Simulation results show that the proposed scheme has much better performance than the available noncoherent combining method, and can accommodate more active ranging users simultaneously in each cell.

This paper describes numerical analyses of the distance-dependent gain variation that exists in gain measurements based on the Friis transmission formula for typical broadband antennas, including double-ridged guide horn and log-periodic dipole array antennas. The analyses are performed by simulating gain measurements using the method of moments with higher-order basis functions and the finite integration method. In addition, we propose approximate techniques to determine the antenna phase center by exploiting the distance dependence of the gain. Simulation and experimental results show the effectiveness of using the location of the phase center to accurately determine the far-field gain at reduced antenna separation distances.

In this paper, we study the feasibility of a batteryless wireless sensor supplied with energy by using microwave power transmission (MPT). If we perform co-channel operation of MPT and wireless local area networks (WLANs) for the sake of spectral efficiency, a time division method for MPT and WLAN communications is required to avoid serious interference from MPT to WLAN data transmissions. In addition, to reduce the power consumption of a sensor, the use of power-save operation of the sensor is desirable. We proposed a scheduling scheme that allocates time for MPT and WLAN communications. Specifically, in the proposed scheduling system, an energy source transmits microwave power to a sensor station except when the sensor station transmits data frames or receives beacon frames. In addition, in the proposed scheduling system, we force the remaining energy of the sensor station to converge to a maximum value by adjusting the time interval of data transmission from the sensor station such that the power consumption of the sensor station is reduced. On the basis of the proposition, we implemented a scheduling system and then confirmed that it performed successfully in the conducted experiments. Finally, we discussed the feasibility of the proposed scheduling scheme by evaluating the coverage and then showed that the scheduling scheme can be applied to closed space or room.

In this paper, we propose a joint transmit and receive linear filtering based on minimum mean square error criterion (joint Tx/Rx MMSE filtering) for single-carrier (SC) multiple-input multiple-output (MIMO) transmission. Joint Tx/Rx MMSE filtering transforms the MIMO channel to the orthogonal eigenmodes to avoid the inter-antenna interference (IAI) and performs MMSE based transmit power allocation to sufficiently suppress the inter-symbol interference (ISI) resulting from the severe frequency-selectivity of the channel. Rank adaptation and adaptive modulation are jointly introduced to narrow the gap of received signal-to-interference plus noise power ratio (SINR) among eigenmodes. The superiority of the SC-MIMO transmission with joint Tx/Rx MMSE filtering and joint rank adaptation/adaptive modulation is confirmed by computer simulation.

This paper presents a method to seamlessly extend the coverage of energy supply field for wireless sensor networks in order to free sensors from wires and batteries, where the multi-point scheme is employed to overcome path-loss attenuation, while the carrier shift diversity is introduced to mitigate the effect of interference between multiple wave sources. As we focus on the energy transmission part, sensor or communication schemes are out of scope of this paper. To verify the effectiveness of the proposed wireless energy transmission, this paper conducts indoor experiments in which we compare the power distribution and the coverage performance of different energy transmission schemes including conventional single-point, simple multi-point and our proposed multi-point scheme. To easily observe the effect of the standing-wave caused by multipath and interference between multiple wave sources, 3D measurements are performed in an empty room. The results of our experiments together with those of a simulation that assumes a similar antenna setting in free space environment show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are limited by path-loss, standing-wave created by multipath and interference between multiple wave sources. On the other hand, the proposed scheme can overcome power attenuation due to the path-loss as well as the effect of standing-wave created by multipath and interference between multiple wave sources.

In this paper, we propose a scalable connection-based time division multiple access architecture for wireless NoC. In this architecture, only one-hop transmission is needed when a packet is transmitted from one wired subnet to another wired subnet, which improves the communication performance and cuts down the energy consumption. Furthermore, by carefully designing the central arbiter, the bandwidth of the wireless channel can be fully used. Simulation results show that compared with the traditional WCube wireless NoC architecture, the proposed architecture can greatly improve the network throughput, and cut down the transmission latency and energy consumption with a reasonable area overhead.

A Decision Diagram Machine (DDM) is a special-purpose processor that has special instructions to evaluate a decision diagram. Since the DDM uses only a limited number of instructions, it is faster than the general-purpose Micro Processor Unit (MPU). Also, the architecture for the DDM is much simpler than that for an MPU. This paper presents a packet classifier using a parallel EVMDD (k) machine. To reduce computation time and code size, first, a set of rules for a packet classifier is partitioned into groups. Then, the parallel EVMDD (k) machine evaluates them. To further speed-up for the standard EVMDD (k) machine, we propose the prefetching EVMDD (k) machine which reads both the index and the jump address at the same time. The prefetching EVMDD (k) machine is 2.4 times faster than the standard one using the same memory size. We implemented a parallel prefetching EVMDD (k) machine consisting of 30 machines on an FPGA, and compared it with the Intel's Core i5 microprocessor running at 1.7GHz. Our parallel machine is 15.1-77.5 times faster than the Core i5, and it requires only 8.1-58.5 percents of the memory for the Core i5.

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.

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.