We propose an image restoration technique that uses multiple image integration. The detail of the dark area when acquiring a dark scene is often deteriorated by sensor noise. Simple image integration inherently has the capability of reducing random noises, but it is especially insufficient in scenes that have a dark area. We introduce a novel image integration technique that optimizes the weights for the integration. We find the optimal weight map by solving a convex optimization problem for the weight optimization. Additionally, we apply the proposed weight optimization scheme to a single-image super-resolution problem, where we slightly modify the weight optimization problem to estimate the high-resolution image from a single low-resolution one. We use some of our experimental results to show that the weight optimization significantly improves the denoising and super-resolution performances.

Circular Polarized Optical OFDM (CPO-OFDM) is a system that applies OFDM to optical wireless communications. This system separates OFDM signals into positive and negative signals and converts these signals into left-handed and right-handed polarization and then multiplexes the resulting polarized signals. In CPO-OFDM, the separated signals must be combined at the receiver. Then, as a noise-reduction method, the comparison method compares the signal amplitudes of the positive and negative signals and uses the signal having the larger amplitude as the received signal. However, if we use the comparison method when the received signals have background light, the combined signals are distorted. In the present paper, we herein report a method by which the receiver estimates the amplitude of the background light and then removes the background light, which is easily accomplished. Furthermore, we also report a theoretical method for analyzing the bit error rate (BER). We develop a closed form of the theoretical formula for the BER in an additive white Gaussian noise (AWGN) channel. By using this formula and through numerical integration, we investigate the theoretical BER for a scintillation channel. We compare the results of the theoretical analysis with those of the simulations. As a result, the theoretical BER is generally coincident with the BER obtained through simulation. Even if we use the closed-form formula, we can derive the BER with sufficient accuracy.

We deal with the scattering of a plane wave by the end-face of a waveguide system by the numerical method based on the sinc function and calculate the electric field on the end-face. It is shown that the results obtained analytically by the perturbation method are in relatively good agreement with the numerical results.

This work presents an approximate global optimization method for image halftone by fusing multi-scale information of the tree model. We employ Gaussian mixture model and hidden Markov tree to characterized the intra-scale clustering and inter-scale persistence properties of the detailed coefficients, respectively. The model of multiscale perceived error metric and the theory of scale-related perceived error metric are used to fuse the statistical distribution of the error metric of the scale of clustering and cross-scale persistence. An Energy function is then generated. Through energy minimization via graph cuts, we gain the halftone image. In the related experiment, we demonstrate the superior performance of this new algorithm when compared with several algorithms and quantitative evaluation.

This paper deals with the security of chaos-based “true” random number generators (RNG)s. An attack method is proposed to analyze the security weaknesses of chaos-based RNGs and its convergence is proved using a master slave synchronization scheme. Attack on a RNG based on a double-scroll attractor is also presented as an example. All secret parameters of the RNG are revealed where the only information available is the structure of the RNG and a scalar time series observed from the double-scroll attractor. Simulation and numerical results of the proposed attack method are given such that the RNG doesn't fulfill NIST-800-22 statistical test suite, not only the next bit but also the same output bit stream of the RNG can be reproduced.

In this letter, we propose a blind adaptive algorithm for joint compensation of inter-block interference (IBI) and frequency-dependent IQ imbalance using a single time-domain equalizer. We combine the MERRY algorithm for IBI suppression with the differential constant modulus algorithm to compensate for IQ imbalance. The effectiveness of the proposed algorithm is shown through computer simulations.

The sliding discrete Fourier transform (DFT) is a well-known algorithm for obtaining a few frequency components of the DFT spectrum with a low computational cost. However, the conventional sliding DFT cannot be applied to practical conditions, e.g., using the sine window and the zero-padding DFT, with preserving the computational efficiency. This paper discusses the extension of the sliding DFT to such cases. Expressing the window function by complex sinusoids, a recursive algorithm for computing a frequency component of the DFT spectrum using an arbitrary sinusoidal window function is derived. The algorithm can be easily extended to the zero-padding DFT. Computer simulations using very long signals show the validity of our algorithm.

In this paper, we present a weighted-polarization wearable multiple-input multiple-output (MIMO) antenna that is based on radio-frequency (RF) signal processing to realize ultra-high-speed and high-capacity mobile communications. The proposed antenna is comprised of three orthogonal dipoles, two of which can be selected according to a weight function in different usage scenarios. The weight function is determined by considering the variation in the cross-polarization power ratio (XPR) and the antenna inclination angle which depend on the radio-propagation environment and human motion. To confirm the suitability of the proposed antenna, we perform preliminary experiments to evaluate the channel capacity of a weighted-polarization wearable MIMO antenna with an arm-swinging dynamic phantom. The measured and analytical results are in good agreement, which verifies the effectiveness of the proposed antenna. We demonstrate that the proposed antenna is suitable for realizing gigabit mobile communications in future wearable MIMO applications.

This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.

Currently there is not any prospect of realizing quantum computers which can compute prime factorization, which RSA relies on, or discrete logarithms, which ElGamal relies on, of practical size. Additionally the rapid growth of Internet of Things (IoT) is requiring practical public key cryptosystems which do not use exponential operation. Therefore we constituted a cryptosystem relying on the difficulty of factoring the product of two large prime numbers, based on the Chinese Remainder Theorem, fully exploiting another strength of MPKC that exponential operation is not necessary. We evaluated its security by performing the Gröbner base attacks with workstations and consequently concluded that it requires computation complexity no less than entirely random quadratic polynomials. Additionally we showed that it is secure against rank attacks since the polynomials of central map are all full rank, assuming the environment of conventional computers.

Nonnegative matrix factorization (NMF) is one of the most popular tools for speech enhancement. In this letter, we present an improved semi-supervised NMF (ISNMF)-based speech enhancement algorithm combining techniques of noise estimation and Incremental NMF (INMF). In this approach, fixed speech bases are obtained from training samples offline in advance while noise bases are trained on-the-fly whenever new noisy frame arrives. The INMF algorithm is adopted for noise bases learning because it can overcome the difficulties that conventional NMF confronts in online processing. The proposed algorithm is real-time capable in the sense that it processes the time frames of the noisy speech one by one and the computational complexity is feasible. Four different objective evaluation measures at various signal-to-noise ratio (SNR) levels demonstrate the superiority of the proposed method over traditional semi-supervised NMF (SNMF) and well-known robust principal component analysis (RPCA) algorithm.

There is a strong push towards the ultra-realistic presentation of multimedia contents made possible by the latest advances in computational and signal processing technologies. Three-dimensional sound presentation is necessary to convey a natural and rich multimedia experience. Promising ways to achieve this include the sound field reproduction technique known as high-order Ambisonics (HOA). While these advanced methods are now within the capabilities of consumer-level processing systems, their adoption is hindered by the lack of contents. Production and coding of the audio components in multimedia focus on traditional formats such as stereophonic sound. Mainstream audio codecs and media such as CDs or DVDs do not support advanced, rich contents such as HOA encodings. To ameliorate this problem and speed up the adoption of spatial sound technologies, this paper proposes a novel way to downmix HOA contents into a stereo signal. The resulting data can be distributed using conventional methods such as audio CDs or as the audio component of an internet video stream. The results can be listened to using legacy stereo reproduction systems. However, they include spatial information encoded as the inter-channel level and phase differences. The proposed method consists of a downmixing filterbank which independently modulate inter-channel differences at each frequency bin. The proposal is evaluated using simple test signals and found to outperform conventional methods such as matrix-encoded surround and the Ambisonics UHJ format in terms of spatial resolution. The proposal can be coupled with a previously presented method to recover HOA signals from stereo recordings. The resulting system allows for the preservation of full-surround spatial information in ultra-realistic contents when they are transferred using a stereo stream. Simulation results show that a compatible decoder can accurately recover up to five HOA channels from a stereo signal (2nd order HOA data in the horizontal plane).

Many recent studies have focused on leveraging rich information types to increase useful information for improving fault localization effectiveness. However, they rarely investigate the impact of information richness on fault localization to give guidance on how to enrich information for improving localization effectiveness. This paper presents the first systematic study to fill this void. Our study chooses four representative information types and investigates the relationship between their richness and the localization effectiveness. The results show that information richness related to frequency execution count involves a high risk of degrading the localization effectiveness, and backward slice is effective in improving localization effectiveness.

A double layer stacked patch antenna with a size of 200×200×48mm3 is proposed in this investigation. To achieve a broad CP bandwidth that can cover universal UHF RFID applications (840-960MHz), a slot loaded circular patch antenna fed by an L-shaped probe is designed as the lower layer (main patch), while the top layer (parasitic patch) is a simple circular patch loaded with a cross-slot of dissimilar arm lengths. Besides demonstrating a broad 10-dB return loss bandwidth of 16% (823-966MHz) and a CP bandwidth (3-dB axial ratio) of 14.0% (837-963MHz), the proposed antenna also yields maximum gain and minimum radiation efficiency of 8.8dBic and 85%, respectively, across the universal UHF RFID bands.

In this paper, a method for designing of Incremental Granular Model (IGM) based on integration of Linear Regression (LR) and Linguistic Model (LM) with the aid of fuzzy granulation is proposed. Here, IGM is designed by the use of information granulation realized via Context-based Interval Type-2 Fuzzy C-Means (CIT2FCM) clustering. This clustering approach are used not only to estimate the cluster centers by preserving the homogeneity between the clustered patterns from linguistic contexts produced in the output space, but also deal with the uncertainty associated with fuzzification factor. Furthermore, IGM is developed by construction of a LR as a global model, refine it through the local fuzzy if-then rules that capture more localized nonlinearities of the system by LM. The experimental results on two examples reveal that the proposed method shows a good performance in comparison with the previous works.

In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.

To design a wireless sensor network for farms, it is necessary to understand and predict the effect of vegetation. In this study, the change in the propagation loss characteristics in 920-MHz band is examined during the growth of mulberry bushes. The received signal strength indicator (RSSI) is measured as a function of the distance between the transmitting antenna (Tx) and the receiving antenna (Rx) in a 50×50m mulberry field. The Tx and Rx are placed at a height of 1.5m. Moreover, the horizontal and vertical polarizations are measured and the differences are shown. Three empirical vegetation attenuation models are introduced, and the measured data have been fitted to each model. The results show that the non-zero gradient model is the best model at predicting the vegetation attenuation in a mulberry farm regardless of the polarization or mulberry growth. It is found that the attenuation dependence on the plant height is linear. Furthermore, the results have revealed that the horizontal polarization had about 1.5 times as large an effect on the vegetation attenuation as the vertical polarization.

We focus on the feature transform approach as one methodology for biometric template protection, where the template consists of the features extracted from the biometric trait. This study considers some properties of the unitary (including orthogonal) transform-based template protection in particular. It is known that the Euclidean distance between the templates protected by a unitary transform is the same as that between original (non-protected) ones as a property. In this study, moreover, it is shown that it provides the same results in l2-norm minimization problems as those of original templates. This means that there is no degradation of recognition performance in authentication systems using l2-norm minimization. Therefore, the protected templates can be reissued multiple times without original templates. In addition, a DFT-based template protection scheme is proposed as an unitary transform-based one. The proposed scheme enables to efficiently generate protected templates by the FFT, in addition to the useful properties. It is also applied to face recognition experiments to evaluate the effectiveness.

An algorithm that finds a set of real-valued approximately-zero correlation zone (AZCZ) sequences is proposed on the basis of the concept of feedback-controlled direct-sequence code-division multiple access (FC/DS-CDMA). It is known that ordinary algorithms can construct low correlation zone (LCZ) and zero correlation zone (ZCZ) sequence sets in which the choices of the number of sequences, sequence length, and LCZ or ZCZ length are limited. It is shown that the proposed algorithm finds AZCZ sequence sets by a numerical method under arbitrary conditions. The properties of AZCZ sequence sets are evaluated in terms of the autocorrelation and cross-correlation functions. It is shown that the periodic autocorrelation and cross-correlation functions take small values within a designated AZCZ. It is also shown that we can construct approximately-perfect sequences that have approximately ideal autocorrelation functions and new sequence sets that have multiple AZCZs using the proposed algorithm.

Satellite-borne or aircraft-borne synthetic aperture radar (SAR) is useful for high resolution imaging analysis for terrain surface monitoring or surveillance, particularly in optically harsh environments. For surveillance application, there are various approaches for automatic target recognition (ATR) of SAR images aiming at monitoring unidentified ships or aircraft. In addition, various types of analyses for full polarimetric data have been developed recently because it can provide significant information to identify structure of targets, such as vegetation, urban, sea surface areas. ATR generally consists of two processes, one is target feature extraction including target area determination, and the other is classification. In this paper, we propose novel methods for these two processes that suit full polarimetric exploitation. As the target area extraction method, we introduce a peak signal-to noise ratio (PSNR) based synthesis with full polarimetric SAR images. As the classification method, the circular polarization basis conversion is adopted to improve the robustness especially to variation of target rotation angles. Experiments on a 1/100 scale model of X-band SAR, demonstrate that our proposed method significantly improves the accuracy of target area extraction and classification, even in noisy or target rotating situations.