The high-resolution frequency estimators most commonly used, such as Least Square (LS) method based on AR model, MVSE, MUSIC and ESPRIT, determine estimates of the sinusoidal frequencies from the sample noise-corrupted data. In this paper, a new frequency estimation method named Pole-Placement Least Square (PPLS) is presented, which is a modified LS method with a certain number of model poles restricted to the unit circle. The statistical performance of PPLS is studied numerically, and compared with the Cramer-Rao bound as well as the statistical performance corresponding to the LS methods. PPLS is shown to have higher resolution than the conventional LS method. The relationship between poles location and its resolution is also discussed in detail.

The current paper presents an effective deblocking algorithm for block-based coded images using singularity detection in a wavelet transform. Blocking artifacts appear periodically at block boundaries in block-based coded images. The local maxima of a wavelet transform modulus detect all singularities, including blocking artifacts, from multiscale edges. Accordingly, the current study discriminates between a blocking artifact and an edge by estimating the Lipschitz regularity of the local maxima and removing the wavelet transform modulus of a blocking artifact that has a negative Lipschitz regularity exponent. Experimental results showed that the performance of the proposed algorithm was objectively and subjectively superior.

Passification of a non-square linear system is considered by using a parallel feedforward compensator (PFC) and a squaring gain matrix. In contrast to the previous result, a technical assumption is removed by modifying the structure of the PFC. As a result, the broader class of non-square systems can be made passive by the proposed design method. Using the static output feedback (SOF) algorithms, the input-dimensional PFC and the squaring matrix can be designed systematically. The effectiveness of the proposed method is illustrated by practical system examples in the control literature.

A fuzzy-like phenomenon in a dynamic neural network is demonstrated and analyzed. The network operates as a dynamic associative memory. Each neuron of the dynamic neural network has an all-or-none output and exponentially decaying refractoriness. When several related patterns are stored in the dynamic neural network and an external stimulus with a property shared by two of the stored patterns is applied to the neural network, the output of the neural network dynamically transits between the two stored patterns. The frequency ratio that the network visits the two stored patterns is dependent on the ratio of the Hamming distances between the external pattern and the two stored patterns. This phenomenon is similar to the human decision-making process, some of which characteristics can be described by fuzzy set theory. A framework for the analysis of this phenomenon is proposed, and is used to derive sufficient conditions which ensure the dynamical transition between the two stored patterns. The properties of the transition in the network are also discussed.

This paper considers a transaction-based multi-server system with rejuvenation, and derive the optimal software rejuvenation policies under some system dependability measures; the steady-state availability, the probability of transaction loss and the upper bound of mean response time on transactions. We compare the system configuration based on a single-server with that based on a multi-server in terms of the software rejuvenation scheme. In numerical examples, we calculate the optimal software rejuvenation timing and its associated dependability measure, and refer to the effect of preventive maintenance in the transaction-based multi-server software systems.

This paper presents a Field-Programmable Digital Filter (FPDF) IC that employs carry-propagation-free redundant arithmetic algorithms for faster computation and multiple-valued current-mode circuit technology for high-density low-power implementation. The original contribution of this paper is to evaluate, through actual chip fabrication, the potential impact of multiple-valued current-mode circuit technology on the reduction of hardware complexity required for DSP-oriented programmable ICs. The prototype FPDF fabrication with 0.6 µm CMOS technology demonstrates that the chip area and power consumption can be reduced to 41% and 71%, respectively, compared with the standard binary logic implementation.

This paper presents an algorithm for fingerprint image restoration using Digital Reaction-Diffusion System (DRDS). The DRDS is a model of a discrete-time discrete-space nonlinear reaction-diffusion dynamical system, which is useful for generating biological textures, patterns and structures. This paper focuses on the design of a fingerprint restoration algorithm that combines (i) a ridge orientation estimation technique using an iterative coarse-to-fine processing strategy and (ii) an adaptive DRDS having a capability of enhancing low-quality fingerprint images using the estimated ridge orientation. The phase-only image matching technique is employed for evaluating the similarity between an original fingerprint image and a restored image. The proposed algorithm may be useful for person identification applications using fingerprint images.

This paper presents a new modulation scheme for Very-High Speed Digital Subscriber Lines (VDSL) modem, featuring a Multi-Code Multi-Carrier Code Division Multiple Access (MC2-CDMA) modulation. The system takes advantage from both the CDMA modulation and the Multi-Carrier transmission, and furthermore the channel throughput is increased adopting a multi-code approach. Starting from an overview of this novel scheme, encompassing the transmitter, channel and receiver description, a brief review of the equalization techniques is also considered and a proper bit-loading algorithm is derived to find out the achievable overall channel rate. The aim of this paper, besides introducing this novel scheme, is to demonstrate its suitability for a VDSL environment, where the achievable channel rate represents a real challenge. By means of a further optimisation, a general improvement of the system performance with respect to the standardized Discrete Multi Tone (DMT) modulation is also demonstrated.

We newly propose a stable algorithm for blind source separation (BSS) combining multistage ICA (MSICA) and linear prediction. The MSICA is the method previously proposed by the authors, in which frequency-domain ICA (FDICA) for a rough separation is followed by time-domain ICA (TDICA) to remove residual crosstalk. For temporally correlated signals, we must use TDICA with a nonholonomic constraint to avoid the decorrelation effect from the holonomic constraint. However, the stability cannot be guaranteed in the nonholonomic case. To solve the problem, the linear predictors estimated from the roughly separated signals by FDICA are inserted before the holonomic TDICA as a prewhitening processing, and the dewhitening is performed after TDICA. The stability of the proposed algorithm can be guaranteed by the holonomic constraint, and the pre/dewhitening processing prevents the decorrelation. The experiments in a reverberant room reveal that the algorithm results in higher stability and separation performance.

Progress in WDM transmission technology and the development of optical cross-connect systems has made optical backbone networks a reality. The conventional planning methodologies for such optical backbone networks calculate optimum light-path arrangements to minimize the network cost under the condition that the number of demanded light-paths is given in advance. However, the light-path demand varies according to the light-path prices. Thus, a new planning methodology for the optical backbone networks is necessary to optimize the light-path prices and to maximize the profit obtained from the network. This paper proposes a new planning methodology for the survivable optical networks. This methodology is based on economic theory for competitive markets involving plural kinds of commodities. Using this methodology, the optimum light-path prices can be decided to maximize the obtained profit. A numerical example is presented to show that the obtained profit can be improved by preparing various light-path classes with different recovery modes and introducing an appropriate light-path pricing according to the reliability of each light-path class.

This paper studies the local Poisson property of aggregated IP traffic. First, it describes the scenario where IP traffic presents a Poisson-like characteristic within some limited range of time scales when packets from independent traffic streams are aggregated. Each of the independent traffic streams corresponds to a series of correlated IP packets such as those of a transport connection. Since the Poisson-like characteristic is observed only within some limited range of time scales, we call this characteristic the local Poisson property. The limited range of time scales of the local Poisson property can be estimated from a network configuration and characteristics of transport connections. Second, based on these observations, we seek the possibility to apply an ordinary Poisson process to evaluation of the packet loss probability in IP networks. The analytical investigation, where IP traffic is modeled by a superposition of independent branching Poisson processes that presents the local Poisson property, suggests that the packet loss probability can be estimated by a finite-buffer queue with a Poisson process when the buffer size is within a certain range. The investigation is verified by simulations. These findings expand the applicability of conventional Poisson-based approaches to IP network design issues.

This paper addresses the routing and wavelength assignment (RWA) problem in a wavelength routed all optical network. One of the main issues is the assignment of the limited number of wavelengths over each physical fiber connection so that high aggregate capacity can be achieved. In a typical mesh topology, this problem has been shown to be NP-hard. In this paper, we propose a new heuristic based algorithm building upon one of the best known wavelength assignment algorithms proposed by Zhang and Acampora. The salient feature of the proposed algorithm is to consider the inherent multihop nature of the underlying mesh topology. We demonstrate that the proposed algorithm reduces the complexity by an order of magnitude, while at the same time achieving significantly lower blocking probability.

Future electric lights will be comprised of white LEDs (Light Emitting Diodes). White LEDs with a high power output are expected to serve in the next generation of lamps. In this paper, an indoor visible data transmission system utilizing white LED lights is proposed. In the proposed system, these devices are used not only for illuminating rooms but also for an optical wireless communication system. This system is suitable for private networks such as consumer communication networks. However, it remains necessary to investigate the properties of white LEDs when they are used as optical transmitters. Based on numerical analyses and computer simulations, it was confirmed that the proposed system could be used for indoor optical transmission.

We report in this paper, the performance of AlGaN/GaN HFETs in the context of high power, low noise and high temperature operations, along with a comparison of their characteristics with other conventional technologies. Finally, a single stage modulator driver for long haul optical communications is presented as an example of application of the GaN-based devices high power handling capabilities.

This paper proposes a technique for indexing, clustering and retrieving images based on their edge features. In this technique, images are decomposed into several frequency bands using the Haar wavelet transform. From the one-level decomposition sub-bands an edge image is formed. Next, the higher order auto-correlation function is applied on the edge image to extract the edge features. These higher order autocorrelation features are normalized to generate a compact feature vector, which is invariant to shift, image size. We used direction cosine as measure of distance not to be influenced by difference of each image's luminance. Then, these feature vectors are clustered by a self-organizing map (SOM) based on their edge feature similarity. The performed experiments show higher precision and recall of this technique than traditional ways in clustering and retrieving images in a large image database environment.

In this paper a digital frequency domain RFI (Radio Frequency Interference) cancellation scheme for DMT (Discrete Multitone) based VDSL (Very high speed Digital Subscriber Line) systems is presented. The proposed algorithm has been optimized and characterized in terms of complexity and performance. Optimizations were also performed from an implementation point of view by deducing key dependencies among our RFI model coefficients that let us drastically reduce the size of the memories involved. System simulations showed the effectiveness of the canceller: in terms of VDSL performance parameters such as bit rate, the optimized cancellation scheme recovers almost totally the performance degradation due to RFI.

There have been numerous studies on the enhancement of the noisy speech signal. In this paper, we propose a completely new speech enhancement method, that is, a filtering of a dissonant frequency based on improved fundamental frequency estimation which is developed in frequency domain. The subjective test results indicate that the proposed method provides a significant gain in audible improvement especially for speech contaminated by colored noise and a husky voice. Therefore if the filter is employed as a pre-filter for speech enhancement, the output speech quality and intelligibility should be greatly enhanced.

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.

We report the investigation of major dispersion mechanisms such as self-heating, trapping, current collapse, and floating-body effects present in AlGaN/GaN HFETs. These effects are analyzed using DC/Pulsed IV, load-pull, low-frequency noise systems, and a cryogenic probe station. This study leads to a better understanding of the device physics, which is critical for accurate large-signal modeling and device optimization.

Weight divided adaptive control method for a microwave FeedForward Power Amplifier (FFPA) is presented. In this adaptive controller, an output signal of a power amplifier is used as reference signal. Additionally, reference signal is divided by the weight of adaptive filter, so that characteristics of the power amplifier, such as temperature dependence, do not have influence on the convergence performances. The proposed adaptive algorithm and the convergence condition are derived analytically and we clarify that the proposed weight divided adaptive algorithm is more stable than the conventional Normalized Least Mean Square (NLMS) algorithm. Then, the convergence condition considering phase calibration error is discussed. The effectiveness of the proposed algorithm are also verified by the nonlinear simulations of the FFPA having AM-AM and AM-PM nonlinearity of GaAsFET.