In a frequency-selective multiple-input multiple-output (MIMO) channel, the optimum transmission is achieved by beamforming with eigenvectors obtained at each discrete frequency point, i.e., an extension of eigenbeam-space division multiplexing (E-SDM). However, the calculation load of eigenvalue decomposition at the transmitter increases in proportion to the number of frequency points. In addition, frequency-independent eigenvectors increase the delay spread of the effective channel observed at the receiver. In this paper, we propose a pseudo eigenvector scheme for the purpose of mitigating the calculation load and maintaining frequency continuity (or decreasing the delay spread). First, we demonstrate that pseudo eigenvectors reduce the delay spread of the effective channels with low computational complexity. Next, the practical performance of the pseudo E-SDM (PE-SDM) transmission is evaluated. The simulation results show that PE-SDM provides almost the same or better performance compared with E-SDM when the receiver employs a time-windowing-based channel estimation available in the low delay spread cases.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear continuous-time systems under typical frequency transformations, such as lowpass-lowpass, lowpass-highpass, lowpass-bandpass, and lowpass-bandstop transformations. Our main result establishes the fact that the second-order modes are invariant under any of these typical frequency transformations. This means that any transformed system that is generated from a prototype system has the same second-order modes as those of the prototype system. We achieve the derivation of this result by describing the state-space equations and the controllability/observability Gramians of transformed systems.

A nonlinear harmonic estimator (NHE) is proposed for extracting a harmonic signal and its fundamental frequency in the presence of white noise. This estimator is derived by applying an extended complex Kalman filter (ECKF) to a multiple sinusoidal model with state-representation and then efficiently specializing it for the case of harmonic estimation. The effectiveness of the NHE is verified using computer simulations.

This paper deals with the singular behavior of the diffraction of transverse magnetic (TM) waves by a perfectly conductive triangular periodic surface at a low grazing limit of incidence. The wave field above the highest excursion of the surface is represented as a sum of Floquet modes with modified diffraction amplitudes, whereas the wave field inside a triangular groove is written as a sum of guided modes with unknown mode amplitudes. Then, two sets of equations are derived for such amplitudes. From the equation sets, all the amplitudes are analytically shown to vanish at a low grazing limit of incidence. From this fact, it is concluded analytically that no diffraction takes place and only reflection occurs at a low grazing limit of incidence for any period length and any triangle height. This theoretical result is verified by a numerical example.

A novel procedure for an efficient and rigorous solution of electromagnetic scattering problems is presented. It is based on the use of universal bases that are obtained by applying the SVD procedure to PO-derived basis functions. These bases, constructed by totally bypassing any matrix-type approach, can be used for all angles of incidence and their use leads to a matrix with relatively small dimensions. The method enables us to solve 2D scattering problems in a computationally efficient and numerically rigorous manner.

A new method to approximate the receive minimum distance is presented. In the proposed approximation, the geometric mean of the singular values of the channel matrix is used instead of the conventional minimum singular value. Numerical experiments show that the proposed approximation has less mean squared error than the minimum singular value bound and outperforms the minimum singular value bound in terms of bit error rate when they are applied to the antenna subgroup selection system.

The diffraction of a transverse magnetic (TM) plane wave by a perfectly conductive surface made up of a periodic array of rectangular grooves is studied by the modal expansion method. It is found theoretically that the reflection coefficient approaches -1 but no diffraction takes place when the angle of incidence reaches a low grazing limit. Such singular behavior is shown analytically to hold for any finite values of the period, groove depth and groove width and is then demonstrated by numerical examples.

This paper introduces a novel MIMO (Multiple Input Multiple Output) communication system having orthogonal dual polarization diversity branches. We have designed a dual polarized circular patch antenna which has two orthogonal polarization ports such as vertical polarization (V) and horizontal polarization (H) on its metal surface. This design makes it works as two independent antennas in multipath environments. By using two dual polarized antennas at both the transmitter and receiver, we designed a dual-polarization 44 MIMO experiment system. This system can be used to investigate the performance of various MIMO transmission methods as well as the performance of adaptive algorithms in indoor multipath environments. To investigate the performance of our experiment system, we carried out a number of MIMO transmission experiments such as space-time-coded transmission having two parallel streams and MIMO eigenmode transmission. We will show the results of those experiments and discuss the advantages of using polarization diversity in MIMO communication system for next generation broadband wireless communication.

Coexisting with many concurrent narrowband services, the performance of UWB systems will be affected considerably by them. Specifically, IEEE 802.11a systems which operate around 5 GHz and overlap the band of UWB signals will interfere with UWB systems significantly. In this paper, a novel narrow-band interferences (NBI) suppression technique based on singular value decomposition (SVD) algorithm for a direct sequence ultra-wideband (DS-UWB) communication system is presented. SVD is used to approximate the interferences which then are subtracted from the received signals. The proposed technique is simple and robust. Simulation results show that the proposed new technique is very effective.

The purpose of the study is to obtain the automatic and optimal matching between a motion-measurement device such as a data glove and an output device such as a dexterous robot hand, where there are many differences in the numbers of degree of freedom, sensor and actuator positions, and data format, by means of motion imitation by the humans. Through the algorithm proposed here, a system engineer or user need no labor of determining the values of gains and parameters to be used. In the system, a subject with data glove imitated the same motion with a dexterous robot hand which was moving according to a certain mathematical function. Autoregressive models were adapted to the matching, where each joint angle in the robot and data glove data of the human were used as object and explanatory variables respectively. The partial regression coefficients were estimated by means of singular value decomposition with a system-noise reduction algorithm utilizing statistical properties. The experimental results showed that the robot hand was controlled with high accuracy with small delay, suggesting that the method proposed in this study is proper and easy way and is adaptive to many other systems between a pair of motion-measurement device and output device.

The release of image processing techniques make image modification and fakery easier. Image fakery, here, is defined as a process to copy a region of source image and paste it onto the destination image, with some post processing methods applied, such as boundary smoothing, blurring, etc. to make it natural. The most important characteristic of image fakery is object copy and paste. In order to detect fake images, this letter introduces a blind detection scheme based on singular value decomposition (SVD). Experimental results also show the effectiveness of the proposed scheme.

This paper presents a new bearing fault detection algorithm based on analyzing singular points of vibration signals using the Haar wavelet. The proposed Haar Fault Detection (HFD) algorithm is compared with a previously-developed algorithm associated with the Morlet wavelet. We also substitute the Haar wavelet with Daubechies wavelets with larger compact supports and evaluate the results. Simulations carried on real data demonstrate that the HFD algorithm achieves a comparable accuracy while having a lower computational cost. This makes the HFD algorithm an appropriate candidate for fast processing of bearing faults.

Non-supersingular elliptic curves are important for the security of pairing-based cryptosystems. But there are few suitable non-supersingular elliptic curves for pairing-based cryptosystems. This letter introduces a method which allows the existing method to generate more non-supersingular elliptic curves suitable for pairing-based cryptosystems when the embedding degree is 6.

This paper provides an overview of research in channel modeling for multiple-input multiple-output (MIMO) data transmission focusing on a radio wave propagation. A MIMO channel is expressed as an equivalent circuit with a limited number of eigenpaths according to the singular-value decomposition (SVD). Each eigenpath amplitude depends on the propagation structure not only of the path direction profiles for both transmission and reception points but also of intermediate regions. Inherent in adaptive control is the problem of instability as a hidden difficulty. In this paper these issues are addressed and research topics on MIMO from a radio wave propagation viewpoint are identified.

Extensive studies have been made of the public key cryptosystems based on multivariate polynomials over F2. However most of the proposed public key cryptosystems based on multivariate polynomials, are proved not secure. In this paper, we propose several types of new constructions of public key cryptosystems based on randomly generated singular simultaneous equations. One of the features of the proposed cryptosystems is that the sets of random singular simultaneous equations significantly enlarges the size of the transformation.

We propose a practical blind channel identification algorithm based on the principal component analysis. The algorithm estimates (1) the channel order, (2) the noise variance, and then identifies (3) the channel impulse response, from the autocorrelation of the channel output signal without using the eigenvalue and singular-value decomposition. The special features of the proposed algorithm are (1) practical method to find the channel order and (2) reduction of computational complexity. Numerical examples show the effectiveness of the proposed algorithm.

This paper provides methods for construction of pairing-based cryptosystems based on non-supersingular elliptic curves.

A new speaker feature extracted from multi-wavelet decomposition for speaker recognition is described. The multi-wavelet decomposition is a multi-scale representation of the covariance matrix. We have combined wavelet transform and the multi-resolution singular value algorithm to decompose eigenvector for speaker feature extraction not at the square matrix. Our results have shown that this multi-wavelet feature introduced better performance than the cepstrum and Δ-cepstrum with respect to the percentages of recognition.

In this paper, a novel Wold decomposition algorithm is proposed to address the issue of deterministic component extraction for texture images. This algorithm exploits the wavelet-based singularity detection theory to process both harmonic a nd evanescent features from frequency domain. This exploitation is based on the 2D Lebesgue decomposition theory. When applying multiresolution analysis techniq ue to the power spectrum density (PSD) of a regular homogeneous random field, its indeterministic component will be effectively smoothed, and its deterministic component will remain dominant at coarse scale. By means of propagating these positions to the finest scale, the deterministic component can be properly extracted. From experiment, the proposed algorithm can obtain results that satisfactorily ensure its robustness and efficiency.

Automatic image inspector inspects the quality of printed circuit boards using image-processing technology. In this study, we change an automatic inspection problem into a problem for detecting the signal singularities. Based on the wavelet theory that the wavelet transform can focus on localized signal structures with a zooming procedure, a novel singularity detection and measurement algorithm is proposed. Singularity positions are detected with the local wavelet transform modulus maximum (WTMM) line, and the Lipschitz exponent is estimated at each singularity from the decay of the wavelet transform amplitude along the WTMM line. According to the theoretical analysis and computer simulation results, the proposed algorithm is shown to be successful for solving the automatic inspection problem and calculating the Lipschitz exponents of signals. These Lipschitz exponents successfully characterize singular behavior of signals at singularities.