It is an important problem to estimate component reliabilities. For a series system due to cost and time constraints associated with failure analysis, all components cannot be investigated and the cause of failure is narrowed to a subset of components in some cases. When such a case occurs, we say that the cause of failure is masked. It is also necessary in some cases to take account of the influence of an environmental stress on all components. In this paper, we consider 2 and 3-component series systems when the component lifelengths are exponentially distributed and an environmental stress follows either a gamma or an inverse Gaussian distribution. We show that the lifelength of the system and the cause of failure are independent of each other. By comparison between the hazard functions in both models, we see that quite short and long lifelengths are more likely to occur in a gamma model than in an inverse Gaussian one. Assuming that the masking probabilities do not depend on which component actually fails, we show that the likelihood function can be factorized into three parts by a reparametrization. For some special cases, some estimators are given in closed-form. We use the computer failure data to see that our model is useful to analyze the real masked data. As compared with the Kaplan-Meier estimator, our models fit this computer data better than no environmental stress model. Further, we determine a suitable model using AIC. We see that the gamma model is fitted to the data better than the inverse Gaussian one. From a limited simulation study for a 3-component series system, we see that the relative errors of some estimators are inversely proportional to the square root of the expected number of systems whose cause of failure is identified.

Imaging techniques for robots are important and meaningful in the near future. Pulse radar systems have a great potential for shape estimation and locationing of targets. They have an advantage that they can be used even in critical situations where optical techniques cannot be used. It is thus required to develop high-resolution imaging algorithms for pulse radar systems. High-resolution imaging algorithms utilize the carrier phase of received signals. However, their estimation accuracy suffers degradation due to phase rotation of the received signal because the phase depends on the shape of the target. In this paper, we propose a phase compensation algorithm for high-resolution pulse radar systems. The proposed algorithm works well with SEABED algorithm, which is a non-parametric algorithm of estimating target shapes based on a reversible transform. The theory is presented first and numerical simulation results follow. We show the estimation accuracy is remarkably improved without sacrificing the resolution using the proposed algorithm.

One of the categories of decoding techniques for DFT codes in erasure channels is the class of iterative algorithms. Iterative algorithms can be considered as kind of alternating mapping methods using the given information in a repetitive way. In this paper, we propose a new iterative method for decoding DFT codes. It will be shown that the proposed method outperforms the well-known methods such as Wiley/Marvasti, and ADPW methods in the decoding of DFT codes in erasure channels.

This paper proposes a method of improving demodulation performance for chaotic synchronization based multiplex communications systems. In a conventional system, the number of data demodulated correctly is limited because transmitted chaotic signals interfere with each other. The proposed system uses a generalized inverse of a matrix formed from chaotic signals at the transmitter. Since this completely cancels the interference between chaotic signals, demodulation performance is greatly improved. The proposed system has the following features: A simple correlation receiver suitable for small terminals can be used; The magnitude of the correlator output is constant for binary data transmission; Analog information data can also be transmitted. Two methods to reduce the peak-to-average power ratio of the transmitted signal are presented.

Environment measurement is an important issue for various applications including household robots. Pulse radars are promising candidates in a near future. Estimating target shapes using waveform data, which we obtain by scanning an omni-directional antenna, is known as one of ill-posed inverse problems. Parametric methods such as Model-fitting method have problems concerning calculation time and stability. We propose a non-parametric algorithm for high-resolution estimation of target shapes in order to solve the problems of parametric algorithms.

In this paper we propose a new blind adaptive compensator associated with the inverse QRD-RLS (IQRD-RLS) algorithm to adaptively estimate the parameters, related to the effects of gain/phase imbalance and DC offsets occur in the Quadrature demodulator, for compensation. In this new approach the power measurement of the received signal is employed to develop the blind adaptation algorithm for compensator, it does not require any reference signal transmitted from the transmitter and possess the fast convergence rate and better numerical stability. To verify the great improvement, in terms of reducing the effects of the imbalance and offset, over existing techniques computer simulation is carried out for the coherent 16 PSK-communication system. We show that the proposed blind scheme has rapidly convergence rate and the smaller mean square error in steady state.

An IIR digital low pass filter with flat monotonic passband, equiripple stopband and narrower transition bandwidth than that of Inverse Chebyshev digital filters of the same order is designed. The requisite equiripple stopband is realized by designing the filter in Deczkeys' w-plane. The characteristic functions are designed so as to have a root of multiplicity n at ω = 0 to ensure the n degree of flatness of the passband, and to have a pair of complex conjugate roots with coordinates constrained such that the magnitude response of the passband attenuates monotonically. The freedom in the coordinate of the complex conjugate roots is exploited to minimize the transition bandwidth. The equations are derived that give the minimum transition bandwidth of the proposed filter, which is considerably narrower than that of Inverse Chebyshev filters. It is showen through practical numerical examples that the order of the proposed filter is as low as half that of the Inverse Chebyshev filter satisfying the same specification.

This paper provides a review on the optimal design of photonic bandgap structures by inverse problem techniques. An overview of inverse problems techniques is given, with a special focus on topology design methods. A review of first applications of inverse problems techniques to photonic bandgap structures and waveguides is given, as well as some model problems, which provide a deeper insight into the structure of the optimal design problems.

We propose a public-key primitive modulo pkq based on the RSA primitive. The decryption process of the proposed scheme is faster than those of two variants of PKCS #1 version 2.1, namely the RSA cryptosystem using Chinese remainder theorem (CRT) and the Multi-Prime RSA. The message M of the proposed scheme is decrypted from M mod pk and M mod q using the CRT, where we apply the Hensel lifting to calculate M mod pk from M mod p that requires only quadratic complexity ((log2p)2). Moreover, we propose a trick that avoids modular inversions used for the Hensel lifting, and thus the proposed algorithm can be computed without modular inversion. We implemented in software both the proposed scheme with 1024-bit modulus p2q and the 1024-bit Multi-Prime RSA for modulus p1p2p3, where p,q,p1,p2,p3 are 342 bits. The improvements of the proposed scheme over the Multi-Prime RSA are as follows: The key generation is about 49% faster, the decryption time is about 42% faster, and the total secret key size is 33% smaller.

In this paper, an efficient optimization algorithm for solving the inverse problem of a two-dimensional lossless homogeneous dielectric object is investigated. A lossless homogeneous dielectric cylinder of unknown permittivity scatters the incident wave in free space and the scattered fields are recorded. Based on the boundary condition and the incident field, a set of nonlinear surface integral equation is derived. The imaging problem is reformulated into optimization problem and the steady-state genetic algorithm is employed to reconstruct the shape and the dielectric constant of the object. Numerical results show that the permittivity of the cylinders can be successfully reconstructed even when the permittivity is fairly large. The effect of random noise on imaging reconstruction is also investigated.

Making up an electromagnetic wave simulator based on the FEM is tried, which may run on some widely used platforms by use of Java and a single commercial tool. Since the codes and configuration files to be created for this simulator are common, one can construct the simulator running on the platforms at the same time. Using this simulator, the transmission properties of two- and three-dimensional waveguide discontinuities in optical and microwave waveguides are analyzed, the inverse problem in material constant measurement is solved, and the computed results are presented including plots of the electric field distribution.

In this paper, a high-performance pipelining architecture for 2-D inverse discrete wavelet transform (IDWT) is proposed. We use a tree-block pipeline-scheduling scheme to increase computation performance and reduce temporary buffers. The scheme divides the input subbands into several wavelet blocks and processes these blocks one by one, so the size of buffers for storing temporal subbands is greatly reduced. After scheduling the data flow, we fold the computations of all wavelet blocks into the same low-pass and high-pass filters to achieve higher hardware utilization and minimize hardware cost, and pipeline these two filters efficiently to reach higher throughput rate. For the computations of N N-sample 2-D IDWT with filter length of size K, our architecture takes at most (2/3)N2 cycles and requires 2N(K-2) registers. In addition, each filter is designed regularly and modularly, so it is easily scalable for different filter lengths and different levels. Because of its small storage, regularity, and high performance, the architecture can be applied to time-critical image decompression.

The objective of this study was to explore suitable spatial filters for inverse estimation of cortical potentials from the scalp electroencephalogram. The effect of incorporating noise covariance into inverse procedures was examined by computer simulations. The parametric projection filter, which allows inverse estimation with the presence of information on the noise covariance, was applied to an inhomogeneous three-concentric-sphere model under various noise conditions in order to estimate the cortical potentials from the scalp potentials. The present simulation results suggest that incorporation of information on the noise covariance allows better estimation of cortical potentials, than inverse solutions without knowledge about the noise covariance, when the correlation between the signal and noise is low. The method for determining the optimum regularization parameter, which can be applied for parametric inverse techniques, is also discussed.

This letter outlines a scheme to produce a wider robust bandwidth, with better approximations to the perfect reproduction of pre-recorded acoustic signals. Multi-parameter inverse filtering method is proposed in the virtual sound imaging system for improving the robustness performance. The superiority of this new type of inverse filter is demonstrated on a 3-speaker system.

Evaluating the generalization performance of learning machines without using additional test samples is one of the most important issues in the machine learning community. The subspace information criterion (SIC) is one of the methods for this purpose, which is shown to be an unbiased estimator of the generalization error with finite samples. Although the mean of SIC agrees with the true generalization error even in small sample cases, the scatter of SIC can be large under some severe conditions. In this paper, we therefore investigate the causes of degrading the precision of SIC, and discuss how its precision could be improved.

To sample a band-limited analog signal directly from the high frequency down to the baseband for the digital signal processing with significantly reduced computation, several concepts of the bandpass sampling are introduced. In this paper, a robust bandpass sampling scheme when there exist frequency deviations due to the channel effect and hardware instability is proposed for practical use, and the effects of the frequency deviations are discussed to select a proper sampling frequency.

In this paper, we propose a passive imaging system for noise-source identification using time-domain waveform sampling. The fundamental concepts are based on optics theory. A waveform of a diffracted field over an entrance pupil is obtained by a digitizing oscilloscope. The phase distributions over the entrance pupil for each frequency are calculated by using Fourier transform of the acquired waveforms. Thus, an image on the focal plane is reconstructed by using inverse Fresnel transform. The most significant advantage of the proposed method is that an image for each frequency can be obtained separately. We confirmed that the proposed method can be used for practical noise-source identification, by experimentally obtaining images for an emission from personal computers.

A new multi-luminance-level subfield method is proposed to reduce the low gray-level contour of an alternate current plasma display panel (AC-PDP). The minimum or maximum luminance level per sustain-cycle can be altered by simultaneously applying the proper auxiliary short pulses. As a result, the multi-luminance levels per one or two sustain pulse pairs can be expressed by properly adjusting the auxiliary short pulses for the one or two sustain-cycle subfields, thereby suppressing a low gray-level contour of AC-PDP.

We describe a method of compensating temperature fluctuation by a linear-time-warping processing in a sound reproduction system. This technique is applied to impulse responses of room transfer functions, to achieve a high-quality sound reproduction system, particularly one that treats high-frequency components. First, the impulse responses are measured before and after temperature fluctuation, and the former are converted to the latter by the proposed process. Next, we design inverse filters for the system, and evaluate the improvement of the reproduction accuracy and spectrum distortion. By the compensation method, we can improve the reproduction accuracy at any frequency. Moreover, we propose an adaptive algorithm for the estimation of a suitable warping ratio, using the observed signal of reproduced sound obtained at only one control point. Using the proposed algorithm, we can improve the reproduction accuracy at each control point by about 14 dB, in which a difference in temperature is 1.4.

Generalized Pulse Spectrum Technique (GPST) is a method to solve the inverse problems of wave-propagation and diffusion-dominated phenomena, and therefore has been popularly applied in image reconstruction of time-resolved diffuse optical tomography. With a standard GPST for simultaneous reconstruction of absorption and scattering coefficients, the products of the gradients of the Green's function and the photon-density flux, based on the photon-diffusion equation, are required to calculate the diffusion-related Jacobian matrix. The adversities are of two-folds: time-consuming and singular in the field near the source. The latter causes a severe insensitivity of the algorithm to the scattering changes deep inside tissue. To cope with the above difficulties, we propose in this paper a modified GPST algorithm that only involves the Green's function and the photon-density flux themselves in the scattering-related matrix. Our simulated and experimental reconstructions show that the modified algorithm can significantly improve the quality of scattering image and accelerate the reconstruction process, without an evident degradation in absorption image.