The letter deals with direction-of-arrival (DOA) estimation under nonuniform white noise and moderately small signal-to-noise ratios. The proposed approach first uses signal subspace projection for received data vectors, which form an efficient iterative quadratic maximum-likelihood (IQML) approach to achieve fast convergence and high resolution capabilities. In conjunction with a signal subspace selection technique, a more exact signal subspace can be obtained for reducing the nonuniform noise effect. The performance improvement achieved by applying the proposal to the classic IQML method is confirmed by computer simulations.

Over the recent years, a great deal of effort has been made to estimate age from face images. It has been reported that age can be accurately estimated under controlled environment such as frontal faces, no expression, and static lighting conditions. However, it is not straightforward to achieve the same accuracy level in a real-world environment due to considerable variations in camera settings, facial poses, and illumination conditions. In this paper, we apply a recently proposed machine learning technique called covariate shift adaptation to alleviating lighting condition change between laboratory and practical environment. Through real-world age estimation experiments, we demonstrate the usefulness of our proposed method.

We fabricated and evaluated a prototype imaging system using the Simultaneous Frequency-Encoding technique, which is an active imaging technique that is potentially capable of fast frame-frequency imaging using a frequency-scanning antenna with only a single transceiver. The prototype performed simultaneous acquisition of pixels in elevation using Simultaneous Frequency-Encoding and performed a mechanical scan in azimuth. We also studied a ranging technique and incorporated it into the prototype. The ranging technique for Simultaneous Frequency-Encoding must take into account the characteristics of the frequency-scanning antenna, which are fundamental to Simultaneous Frequency-Encoding. We verified that ordinary range processing can be performed before frequency analysis with Simultaneous Frequency-Encoding, giving both range and angular profiles. The prototype was evaluated based on the radiation patterns of a receiver antenna comprising the frequency-scanning antenna and a reflector, on which both the image quality and ranging performance depend. Finally we conducted actual imaging tests and confirmed the capability of through-obstacle imaging. The frame frequency was only 0.1 Hz, which was due to the use of a slow mechanical scan in azimuth. However, assuming electronic beam forming is used instead of the mechanical scan, the frame frequency can be improved to several Hertz.

This study focuses on speaker adaptation techniques for Computer-Assisted Language Learning (CALL). We first investigate the effects and problems of Maximum Likelihood Linear Regression (MLLR) speaker adaptation when used in pronunciation evaluation. Automatic scoring and error detection experiments are conducted on two publicly available databases of Japanese learners' English pronunciation. As we expected, over-adaptation causes misjudgment of pronunciation accuracy. Following the analysis, we propose a novel method, Regularized Maximum Likelihood Regression (Regularized-MLLR) adaptation, to solve the problem of the adverse effects of MLLR adaptation. This method uses a group of teachers' data to regularize learners' transformation matrices so that erroneous pronunciations will not be erroneously transformed as correct ones. We implement this idea in two ways: one is using the average of the teachers' transformation matrices as a constraint to MLLR, and the other is using linear combinations of the teachers' matrices to represent learners' transformations. Experimental results show that the proposed methods can better utilize MLLR adaptation and avoid over-adaptation.

We study problems in computational geometry from the viewpoint of adaptive algorithms. Adaptive algorithms have been extensively studied for the sorting problem, and in this paper we generalize the framework to geometric problems. To this end, we think of geometric problems as permutation (or rearrangement) problems of arrays, and define the "presortedness" as a distance from the input array to the desired output array. We call an algorithm adaptive if it runs faster when a given input array is closer to the desired output, and furthermore it does not make use of any information of the presortedness. As a case study, we look into the planar convex hull problem for which we discover two natural formulations as permutation problems. An interesting phenomenon that we prove is that for one formulation the problem can be solved adaptively, but for the other formulation no adaptive algorithm can be better than an optimal output-sensitive algorithm for the planar convex hull problem. To further pursue the possibility of adaptive computational geometry, we also consider constructing a kd-tree.

A transmitting and receiving modulation MIMO radar system is effective to obtaining 3D resolution without a 2D array and to simplification of the electronic circuits in Tx and Rx array. But the dynamic range of the conventional system is limited by the interchannel interference of the used preferred pair M-sequence codes for Tx and Rx modulation. This paper presents a TRM-MIMO radar system based on orthogonal coded theory. We derive a condition which the Tx and Rx codes doubly modulated at the Tx and Rx arrays should satisfy. The acquisition time and code length is theoretically discussed. The experiments are carried out in order to demonstrate the effectiveness of this method by using a developed TRM-MIMO radar system with Hadamard codes. As the result, it is found that the proposed orthogonal code modulation method achieves more than 20 dB improvement of the dynamic range which is limited due to the interchannel interference of a moving clutter in a conventional system with M-sequence codes. Moreover, 5 times faster acquisition time is achieved.

This paper proposes a novel image segmentation method based on Clausius entropy and adaptive Gaussian mixture model for detecting moving objects in a complex environment. The results suggest that the proposed method performs better than existing methods in extracting the foreground in various video sequences composed of multiple objects, lighting reflections, and background clutter.

In bistatic radar, it is important to suppress the undesired signals such as the direct propagated signal from transmitter and its multipath components. Conventionally, some suppression methods have been proposed. They are categorized into the method using a feedback system and the method which subtracts the replicas of the undesired signals. The former method may have the problem on the convergence of the suppression performance. The latter method requires the precise delay times of the undesired signals. In this paper we propose a new method to detect the target in digital terrestrial TV-based bistatic radar which is based on orthogonal frequency division multiplexing (OFDM), without any information on the undesired signals' delay times. In the proposed method, we adapt a scheme based on maximum signal to noise ratio (MSN) algorithm, which makes signal to interference plus noise ratio (SINR) maximum for the desired signal component. The maximum sensitivity is steered so as to match the path that exhibits the delay which relates to the target position, as if the search beam is steered along the direction in array signal processing. In the proposed method, "nulls" are also formed for other delay components to be suppressed simultaneously. In the frequency domain, the carrier components of the scattered signal divided by those of the reference signal indicate the delays caused by scattering. We call these divided carrier components "normalized received signal." The steered sensitivity and nulls are created by the weight which is applied to the normalized received signal in the frequency domain. We obtain the method to estimate the weight to achieve the maximum SINR in the delay estimation which also includes the compensation for the reduction of the weight's length caused by decorrelation among the delay components. The simulation results show that our proposed method without any information on the undesired signal's delays provides sufficient detection performance for the typical target compared to the conventional one.

Background subtraction is widely used in detecting moving objects; however, changing illumination conditions, color similarity, and real-time performance remain important problems. In this paper, we introduce a sequential method for adaptively estimating background components using Kalman filters, and a novel method for detecting objects using margined sign correlation (MSC). By applying MSC to our adaptive background model, the proposed system can perform object detection robustly and accurately. The proposed method is suitable for implementation on a graphics processing unit (GPU) and as such, the system realizes real-time performance efficiently. Experimental results demonstrate the performance of the proposed system.

ICA (Independent Component Analysis) has a remarkable capability of separating mixtures of stochastic random signals. However, we often face problems of separating mixtures of deterministic signals, especially sinusoidal signals, in some applications such as radar systems and communication systems. One may ask if ICA is effective for deterministic signals. In this paper, we analyze the basic performance of ICA in separating mixtures of complex sinusoidal signals, which utilizes the fourth order cumulant as a criterion of independency of signals. We theoretically show that ICA can separate mixtures of deterministic sinusoidal signals. Then, we conduct computer simulations and radio experiments with a linear array antenna to confirm the theoretical result. We will show that ICA is successful in separating mixtures of sinusoidal signals with frequency difference less than FFT resolution and with DOA (Direction of Arrival) difference less than Rayleigh criterion.

It is known that composable secure commitments, that is, concurrent non-malleable commitments exist in the plain model, based only on standard assumptions such as the existence of claw-free permutations or even one-way functions. Since being based on the plain model, the deniability of them is trivially satisfied, and especially the latter scheme satisfies also adaptivity, hence it is adaptive-deniable-concurrent non-malleable. However, those schemes cannot be said to be practically efficient. We show a practically efficient (string) adaptive-deniable-concurrent commitment scheme is possible under a global setup model, called the Global CRS-KR model.

The effect of DC offset on multi-input multi-output (MIMO) direct transceivers with adaptive modulation (AM) is discussed in this paper. A variable-rate variable-power (VRVP) AM system with perfect channel state information (P-CSI) at both the transmitter and receiver in a MIMO scenario is considered. The DC offset is modeled as a zero mean complex Gaussian distributed random variable. By this modeling of the DC offset, the analytical expression for degraded bit error rate (BER) is derived. To derive this analytical expression, we establish a reasonable approximation. The good agreement between the analytical and simulation results shows that the approximation is valid and confirms the accuracy of the analytical expressions. Moreover, an approach to improve the degraded BER in these systems is introduced. For this purpose, we introduce a design for AM MIMO systems that takes account of DC offset and its effectiveness is confirmed. Throughput analysis for the AM MIMO system in the presence of DC offset is presented in this paper too. An analytical expression for throughput is derived and approximated to a simpler equation. At last, throughput results are compared to the simulation outcomes.

In this paper, the inherent problem of the Hough transform when applied to search radars is considered. This problem makes the detection probability of a target depend on the length of the target line in the data space in addition to the received SNR from it. It is shown that this problem results in a non-uniform distribution of noise power in the parameter space. In other words, noise power in some regions of the parameter space is greater than in others. Therefore, the detection probability of the targets covered by these regions will decrease. Our solution is to modify the Hough detector to remove the problem. This modification uses non-uniform quantization in the parameter space based on the Maximum Entropy Quantization method. The details of implementing the modified Hough detector in a search radar are presented according to this quantization method. Then, it is shown that by using this method the detection performance of the target will not depend on its length in the data space. The performance of the modified Hough detector is also compared with the standard Hough detector by considering their probability of detection and probability of false alarm. This comparison shows the performance improvement of the modified detector.

Locality of high frequency electromagnetic scattering phenomena is embodied and imported to the Method of Moments (MoM) to reduce computational load. The proposed method solves currents on small areas only around inner and edge stationary phase points (SPPs) on the scatterer surfaces. The range of MoM area is explicitly specified in terms of Fresnel zone number as a function of frequency, source and observer positions. Based upon this criterion, scatterer of arbitrary size and shape can be solved with almost frequency independent number of unknowns. In some special cases like focusing systems, locality disappears and the method reduces to the standard MoM. The hybrid method called PO-MoM is complementarily introduced to cope with these cases, where Fresnel zone number with analogous but different definition is used. The selective use of Local-MoM and PO-MoM provides frequency insensitive number of unknowns for general combination of source and observation points. Numerical examples of RCS calculation for two dimensional flat and curved surfaces are presented to demonstrate the accuracy and reduction of unknowns of this method. The Fresnel zone, introduced in the scattering analysis for the first time, is a useful indicator of the locality or the boundary for MoM areas.

In order to reduce the convergence time in an iterative procedure, some gradient based preliminary processes are employed to eliminate outliers. The adaptive variable block size is also introduced to balance the accuracy and computational complexity. Moreover, the use of Canberra distance instead of Euclidean distance illustrates higher performance in measuring motion similarity.

We attempted to estimate subjective scores of the Japanese Diagnostic Rhyme Test (DRT), a two-to-one forced selection speech intelligibility test. We used automatic speech recognizers with language models that force one of the words in the word-pair, mimicking the human recognition process of the DRT. Initial testing was done using speaker-independent models, and they showed significantly lower scores than subjective scores. The acoustic models were then adapted to each of the speakers in the corpus, and then adapted to noise at a specified SNR. Three different types of noise were tested: white noise, multi-talker (babble) noise, and pseudo-speech noise. The match between subjective and estimated scores improved significantly with noise-adapted models compared to speaker-independent models and the speaker-adapted models, when the adapted noise level and the tested level match. However, when SNR conditions do not match, the recognition scores degraded especially when tested SNR conditions were higher than the adapted noise level. Accordingly, we adapted the models to mixed levels of noise, i.e., multi-condition training. The adapted models now showed relatively high intelligibility matching subjective intelligibility performance over all levels of noise. The correlation between subjective and estimated intelligibility scores increased to 0.94 with multi-talker noise, 0.93 with white noise, and 0.89 with pseudo-speech noise, while the root mean square error (RMSE) reduced from more than 40 to 13.10, 13.05 and 16.06, respectively.

An adaptive dimming technique controls both LCD panel transmittance and its backlight luminance adequately and locally according to the input TV signal. The technique reduces the power consumption and also improves the picture quality. However, a steep change in backlight luminance distribution due to the application of the technique causes image degradation around the boundary of the segments when the LCD is viewed from an angle. The main factor of image degradation is the illumination of a pixel by neighboring pixel's corresponding backlight when the LCD is viewed from an angle rather than normal direction. From the subjective evaluation of image quality and computer simulation, it is found that the gradient of the backlight luminance variation to luminance at the border of the segment should be less than 0.022 per pixel in order to suppress the image degradation.

This paper proposes a medium access control (MAC) mechanism for the recently developed IEEE 802.15.4 standard, a promising candidate to become the physical (PHY) and MAC layer standard for Wireless Sensor Networks (WSNs). The main concern in WSNs is the energy consumption, and this paper presents a mechanism that adapts properly the duty cycle operation according to the traffic conditions. Various traffic adaption mechanisms have been presented for the MAC layer of the IEEE 802.15.4. However these conventional mechanisms only consider the temporal traffic fluctuations. The proposed mechanism outperforms the conventional mechanism when applied to cluster-tree based WSNs, because it considers not only the temporal fluctuations but also the spatial (geographical) fluctuations, which are intrinsic characteristics of traffic in WSNs with the cluster tree topology. Evaluations showed that the proposed mechanism achieves less energy consumption than the conventional traffic adaptation mechanism, with maintaining almost the same transmission performance.

We investigate binary sequence pairs with two-level correlation in terms of their corresponding cyclic difference pairs (CDPs). We define multipliers of a cyclic difference pair and present an existence theorem for multipliers, which could be applied to check the existence/nonexistence of certain hypothetical cyclic difference pairs. Then, we focus on the ideal case where all the out-of-phase correlation coefficients are zero. It is known that such an ideal binary sequence pair exists for length υ = 4u for every u ≥ 1. Using the techniques developed here on the theory of multipliers of a CDP and some exhaustive search, we are able to determine that, for lengths υ ≤ 30, (1) there does not exist "any other" ideal/ binary sequence pair and (2) every example in this range is equivalent to the one of length υ = 4u above. We conjecture that if there is a binary sequence pair with an ideal two-level correlation then its in-phase correlation must be 4. This implies so called the circulant Hadamard matrix conjecture.

In this paper, we investigate a multi-packet transmitting and receiving wireless mesh network that uses a multi-antenna set on each node in the network. In wireless mesh networks for accessing the Internet, the target of all traffic generated from distributed nodes is a gateway (GW). Therefore, many packets are concentrated around the GW and the communication channel around the GW is crowded. To prevent packet congestion around the GW, we propose setting an adaptive array antenna on the GW and the relay nodes. We also calculate an appropriate number of antenna elements considering the fair traffic over the whole region, to prevent packet congestion at each node.