This letter investigates the effects of spatial correlation on several multiple antenna schemes in multiuser environments. Using an order statistics upper bound on achievable capacity, we quantify the interaction among spatial correlation, spatial diversity, spatial multiplexing and multiuser diversity. Also, it is verified that the upper bound is tighter than asymptotic capacity when the number of users is relatively small.

Precise estimation of data distribution with a small number of sample patterns is an important and challenging problem in the field of statistical pattern recognition. In this paper, we propose a novel method for estimating multimodal data distribution based on the Gaussian mixture model. In the proposed method, multiple random vectors are generated after classifying the elements of the feature vector into subsets so that there is no correlation between any pair of subsets. The Gaussian mixture model for each subset is then constructed independently. As a result, the constructed model is represented as the product of the Gaussian mixture models of marginal distributions. To make the classification of the elements effective, a graph cut technique is used for rearranging the elements of the feature vectors to gather elements with a high correlation into the same subset. The proposed method is applied to a character recognition problem that requires high-dimensional feature vectors. Experiments with a public handwritten digit database show that the proposed method improves the accuracy of classification. In addition, the effect of classifying the elements of the feature vectors is shown by visualizing the distribution.

This letter proposes a simple k-hop flooding scheme for the temporarily lost child node of a multicast tree in a mobile ad hoc network where a group of nodes move together within a bound. Through simulation, we show that our scheme improves the packet delivery ratio of MAODV to be comparable to the epidemic routing with only small additional duplicate packets.

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.

In this paper, the performance of the induced dimension reduction (IDR) method implemented along with the method of moments (MoM) is described. The MoM is based on a combined field integral equation for solving large-scale electromagnetic scattering problems involving conducting objects. The IDR method is one of Krylov subspace methods. This method was initially developed by Peter Sonneveld in 1979; it was subsequently generalized to the IDR(s) method. The method has recently attracted considerable attention in the field of computational physics. However, the performance of the IDR(s) has hardly been studied or practiced for electromagnetic wave problems. In this study, the performance of the IDR(s) is investigated and clarified by comparing the convergence property and memory requirement of the IDR(s) with those of other representative Krylov solvers such as biconjugate gradient (BiCG) methods and generalized minimal residual algorithm (GMRES). Numerical experiments reveal that the characteristics of the IDR(s) against the parameter s strongly depend on the geometry of the problem; in a problem with a complex geometry, s should be set to an adequately small value in order to avoid the "spurious convergence" which is a problem that the IDR(s) inherently holds. As for the convergence behavior, we observe that the IDR(s) has a better convergence ability than GPBiCG and GMRES(m) in a variety of problems with different complexities. Furthermore, we also confirm the IDR(s)'s inherent advantage in terms of the memory requirements over GMRES(m).

The Maxwell-Wagner type interfacial charging processes were characterized by time-resolved second harmonic generation method (TR-SHG) using three typical organic double-layer devices, i.e., IZO/α-NPD/Alq3/Al for OLED and ITO/PI/α-NPD (or pentacene)/Au for MIM elements. Devices with a PI blocking layer represent one-carrier transport case, while the OLED is a typical two-carrier transport device. It is found that three devices show similar behavior of charging of the electrodes, however, interfacial charging behavior was different from case to case. On the basis of Maxwell-Wagner model, the different transients were analyzed with consideration of carrier species responsible for the interfacial charging. The observed TR-SHG well support the results of I-V measurements.

In this letter, we propose a low-complexity coarse frequency offset estimation scheme in an orthogonal frequency division multiplexing (OFDM) system using non-uniform phased pilot symbols. In our approach, the pilot symbol used for frequency estimation is grouped into a number of pilot subsets so that the phase of pilots in each subset is unique. We show via simulations that such a design achieves not only a low computational load but also comparable performance, when compared to the conventional estimator.

A 2 GHz gain equalizer for analog signal transmission using a novel gain compensation method is described in this paper. This method is based on feedforward compensation by a low-pass filter, which improves the gain-equalizing performance by subtracting low-pass filtered signals from the directly passed signal at the end of a transmission line. The advantage of the proposed method over the conventional one is that the gain is equalized with a smaller THD at higher frequencies by using a low-pass instead of a high-pass filter. In this circuit, the peak gain is adjustable from 0 to 2.4 dB and the frequency of the peak gain can be controlled up to 2 GHz by varying the value of an external capacitor. Also this circuit achieves THD with 5 dB better than the conventional circuits.

Blood pressure is the measurement of the force exerted by blood against the walls of the arteries. Hypertension is a major risk factor of cardiovascular diseases. The systolic and diastolic blood pressures obtained from the oscillometric method could carry clues about hypertension. However, blood pressure is influenced by individual traits such as physiology, the geometry of the heart, body figure, gender and age. Therefore, consideration of individual traits is a requisite for reliable hypertension monitoring. The oscillation waveforms extracted from the cuff pressure reflect individual traits in terms of oscillation patterns that vary in size and amplitude over time. Thus, uniform features for individual traits from the oscillation patterns were extracted, and they were applied to evaluate systolic and diastolic blood pressures using two feedforward neural networks. The measurements of systolic and diastolic blood pressures from two neural networks were compared with the average values of systolic and diastolic blood pressures obtained by two nurses using the auscultatory method. The recognition performance was based on the difference between the blood pressures measured by the auscultation method and the proposed method with two neural networks. The recognition performance for systolic blood pressure was found to be 98.2% for 20 mmHg, 93.5% for 15 mmHg, and 82.3% for 10 mmHg, based on maximum negative amplitude. The recognition performance for diastolic blood pressure was found to be 100% for 20 mmHg, 98.8% for 15 mmHg, and 88.2% for 10 mmHg based on maximum positive amplitude. In our results, systolic blood pressure showed more fluctuation than diastolic blood pressure in terms of individual traits, and subjects with prehypertension or hypertension (systolic blood pressure) showed a stronger steep-slope pattern in 1/3 section of the feature windows than normal subjects. The other side, subjects with prehypertension or hypertension (diastolic blood pressure) showed a steep-slope pattern in front of the feature windows (2/3 section) than normal subjects. This paper presented a novel blood pressure measurement system that can monitor hypertension using personalized traits. Our study can serve as a foundation for reliable hypertension diagnosis and management based on consideration of individual traits.

This work presents a two-stage ordinal optimization theory-based approach for solving the throughput maximization problems with power constraints of sub-carrier assignment and power allocation in multi-user orthogonal frequency division multiplexing uplink systems. In the first stage, a crude but efficient model is employed to evaluate the performance of a sub-carrier assignment pattern and the genetic algorithm is used to search through the huge solution space. In the second stage, an exact model is employed to evaluate s best sub-carrier assignment patterns obtained in stage 1 and form the select subset. Finally, the best one of the select subset is the good enough solution that we seek. Via numerous tests, this work demonstrates the efficiency of the proposed algorithm and compares it with those of other heuristic methods.

This paper proposes a new approach for the joint processing of signal detection and channel estimation based on the expectation-maximization (EM) algorithm in orthogonal frequency division multiplexing (OFDM) mobile communications. Conventional schemes based on the EM algorithm estimate a channel impulse response using Kalman filter, and employ the random walk model or the first-order autoregressive (AR) model to derive the process equation for the filter. Since these models assume that the time-variation of the impulse response is white noise without considering any autocorrelation property, the accuracy of the channel estimation deteriorates under fast-fading conditions, resulting in an increased packet error rate (PER). To improve the accuracy of the estimation of fast-fading channels, the proposed scheme employs a differential model that allows the correlated time-variation to be considered by introducing the first- and higher-order time differentials of the channel impulse response. In addition, this paper derives a forward recursive form of the channel estimation along both the frequency and time axes in order to reduce the computational complexity. Computer simulations of channels under fast multipath fading conditions demonstrate that the proposed method is superior in PER to the conventional schemes that employ the random walk model.

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.

The purpose of this work is to synthesize a three-dimension C60 polymer using photo-polymerization method. The used pristine materials were C60 precipitates prepared by a liquid-liquid interfacial precipitation (LLIP) method. The prepared LLIP material was set in the vacuum and was compressed in the anvil with the pressure of 600 MPa or 7 GPa. The 4th harmonics FEL with the wavelength of 500 nm was irradiated with macro-pulses (the pulse width of 20 µs) containing very short micro-pulses (the pulse width of 200 fs). The Raman Ag(2) peak of C60 molecules in the vicinity of 1469 cm-1 becomes broad and shifts to the lower energy region as proceeding of polymerization. Under high pressure and/or FEL irradiation the LLIP crystal revealed the large red-shift and the increment of the half width of the Raman Ag(2) peak. Furthermore the LLIP crystal mixture with iodine revealed the more distinctive red-shift, ca.13cm-1 because of highly packing of C60 molecules. The C60 molecular accession by LLIP process and/or the photo-assisted hole-doping from iodine were promising conditions to promote the photo-polymerization effectively.

In situ observation of the adsorption process and the states of cytochrome c on glass/solution interfaces, and the functionality of the reduction reaction of adsorbed cytochorome c were performed by using slab optical waveguide (SOWG) spectroscopy. The peak position of the absorption band of cytochorome c adsorbed on a bare glass surface was almost the same as that of that in solution. The cytochorome c adsorbed on glass/solution interface was reduced by sodium dithionite solution. The adsorbed cytochorome c was still maintained its functionality after immobilization.

Iris recognition is an important biometric method for personal identification. The accuracy of an iris recognition system highly depends on the success of an iris segmentation step. In this paper, a robust and accurate iris segmentation algorithm for closed-up NIR eye images is developed. The proposed method addressed problems of different characteristics of iris databases using local image properties. A precise pupil boundary is located with an adaptive thresholding combined with a gradient-based refinement approach. A new criteria, called a local signal-to-noise ratio (LSNR) of an edge map of an eye image is proposed for localization of the iris's outer boundary. The boundary is modeled with a weighted circular integral of LSNR optimization technique. The proposed method is experimented with multiple iris databases. The obtained results demonstrated that the proposed iris segmentation method is robust and desirable. The proposed method accurately segments iris region, excluding eyelids, eyelashes and light reflections against multiple iris databases without parameter tunings. The proposed iris segmentation method reduced false negative rate of the iris recognition system by half, compared to results obtained using Masek's method.

A differential cross-correlation cell ID identification algorithm is proposed for IEEE 802.16e OFDMA cellular system. The cell ID represents the number of the preamble selected by the base station in downlink mode. First, we construct the downlink (DL) preamble structure and signal model with carrier frequency offset (CFO) and channel effects. Next, in order to achieve the initial synchronization, a differential receiver with cross correlation for all preamble patterns is proposed to search for cell ID. Simulation results confirm that the proposed structure is suitable for ITU fading channels and outperforms the conventional cell search system.

We review our recent work on ultra-long-haul wavelength division multiplexed (WDM) transmission with high spectral efficiency (SE) employing tight pre-filtering and multi-symbol detection. We start the discussion with a theoretical evaluation of the SE limit of pre-filtered modulation in optical fiber communication systems. We show that pre-filtering induced symbol correlation generates a modulation with memory and thus, a higher SE limit than that of the original memory-less modulation. We also investigate the merits of utilizing the pre-filtering induced symbol correlation with multi-symbol detection to achieve high SE transmission. We demonstrate transoceanic WDM transmission of a pre-filtered polarization division multiplexed return-to-zero quaternary phased shift keying (PDM-RZ-QPSK) modulation format with multi-symbol detection, achieving 419% SE which is higher than the SE limit of the original memory-less PDM-RZ-QPSK format.

To meet the increasing demand to expand wavelength division multiplexing (WDM) transmission capacity, ultrahigh spectral density coherent optical transmission employing multi-level modulation formats has attracted a lot of attention. In particular, ultrahigh multi-level quadrature amplitude modulation (QAM) has an enormous advantage as regards expanding the spectral efficiency to 10 bit/s/Hz and even approaching the Shannon limit. We describe fundamental technologies for ultrahigh spectral density coherent QAM transmission and present experimental results on polarization-multiplexed 256 QAM coherent optical transmission using heterodyne and homodyne detection with a frequency-stabilized laser and an optical phase-locked loop technique. In this experiment, Raman amplifiers are newly adopted to decrease the signal power, which can reduce the fiber nonlinearity. As a result, the power penalty was reduced from 5.3 to 2.0 dB. A 64 Gbit/s data signal is successfully transmitted over 160 km with an optical bandwidth of 5.4 GHz.

Surface integrity of 3D medical data is crucial for surgery simulation or virtual diagnoses. However, undesirable holes often exist due to external damage on bodies or accessibility limitation on scanners. To bridge the gap, hole-filling for medical imaging is a popular research topic in recent years [1]-[3]. Considering that a medical image, e.g. CT or MRI, has the natural form of a tensor, we recognize the problem of medical hole-filling as the extension of Principal Component Pursuit (PCP) problem from matrix case to tensor case. Since the new problem in the tensor case is much more difficult than the matrix case, an efficient algorithm for the extension is presented by relaxation technique. The most significant feature of our algorithm is that unlike traditional methods which follow a strictly local approach, our method fixes the hole by the global structure in the specific medical data. Another important difference from the previous algorithm [4] is that our algorithm is able to automatically separate the completed data from the hole in an implicit manner. Our experiments demonstrate that the proposed method can lead to satisfactory results.

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.