This paper proposes a fast encoding algorithm for iterated function system (IFS) coding of gray-level homogeneous fractal images. In order to realize IFS coding of high order fractal images, it is necessary to solve a set of simultaneous equations with many unknowns. Solving the simultaneous equations using a multi-dimensional, numerical root-finding method is however very time consuming. As preprocessing of numerical computation, the proposed algorithm employs univariate polynomial manipulation, which requires less computation time than multivariate polynomial manipulation. Moreover, the symmetry of the simultaneous equations with respect to the displacement coefficients enables us to derive an equation with a single unknown from the simultaneous equations using univariate polynomial manipulation. An experimental result is presented to illustrate that the encoding time of the proposed algorithm is about 5 seconds on a personal computer with a 400 MHz Pentium II processor.

We have developed an InP-based monolithic optical frequency discriminator consisting of a temperature-insensitive optical filter and dual photodiodes. This integrated device detects the optical frequency deviation of the input light as differential photocurrent from the dual photodiodes, and the photocurrent is fedback to the light source for frequency stabilization through a differential amplifier. The FSR and extinction ratio of the filter are 50 GHz and 20 dB. The total opto-electronic conversion efficiency is 40%. In a frequency stabilization experiment using the developed discriminator, the frequency fluctuation of a DFB laser was reduced to less than 10 MHz.

In this paper, comparison of various orthogonal transforms in Wiener filtering is discussed. The study involves the family of discrete orthogonal transforms called Complex Hadamard Transform, which has been recently introduced by the same authors. Basic definitions, properties and transformation kernel of Complex Hadamard Transform are also shown.

The problem of transient scattering caused by abrupt extinction of a terminative conducting screen in a waveguide is considered. First, a boundary-value problem is formulated to describe the transient phenomena, the problem in which the boundary condition depends on time. Then, application of the Fourier transformation with respect to time derives a Wiener-Hopf-type equation, which is solved by a commonly known decomposition procedure. The transient fields are obtained through the deformation of the integration path for the inverse transformation and the results are represented in terms of the incomplete Lipschitz-Hankel integrals. Numerical examples showing typical transient phenomena are attached.

A wavelength division multiplexing (WDM) optical path-based Internet protocol (IP) backbone network is proposed as a cost-effective way of realizing robust IP-over-photonic systems. The WDM optical path is based on WDM transmission and wavelength routing. Between end-to-end IP backbone routers, the WDM optical path, a fat and robust optical pipe, is defined across photonic transport systems (PTS's). Tera-bit class PTS's will be required for the future IP backbone network and this level of performance is achievable. Optical layer routing is done at intermediate nodes, so the electrical packet-by-packet routing required by existing systems is eliminated. An optical signal format that permits cost-effective IP packet transmission is presented. WDM optical paths directly accommodate the IP packets via layer-2 frames. The cost-effectiveness of the proposed system, especially for heavy traffic, is demonstrated from the viewpoint of the overall network traffic transport capability and network node cost. The proposed system is as robust as existing systems; e. g. fault/degradation localization mechanism and optical layer network protection one are implemented. Thus the proposed IP-over-photonic system will create cost-effective and robust IP backbone networks.

This paper is concerned with blind identification of a nonminimum phase transfer function model. By over-sampling the output at a higher rate than the input, it is shown that its input-output relation can be described by a single input multiple output model (SIMO) with a common denominator polynomial. Based on the model expression, we present an algorithm to estimate numerator polynomials and common denominator polynomial in a blind manner. Furthermore, identifiability of the proposed scheme is clarified, and some numerical results are given for demonstrating its effectiveness.

WDM transmission experiments over cascaded sections of optical links including wavelength converting 2R-transponders have been carried out in a loop testbed. Using dispersion compensated links and simple direct modulated transponder lasers, up to 11 cascaded crossconnects and 1750 km trunk lines have been bridged with 2.5 Gbit/s NRZ signals. The limitations are given mainly due to the accumulated jitter as it is shown by numerical simulations. The results indicate, that 2R-transponders are a useful approach to a flexible WDM network design using bitrate-transparent wavelength conversion.

Wavelet filters used in usual applications are not time-varying filters. In this paper, we present a novel method to design biorthogonal wavelet filters which are orthogonal to the input signals. We call newly designed filters time-varying lifting wavelet filters (TVLWF). Their feature is to vary the wavelet filters adapting to the input signal by tuning free parameters contained in the lifting scheme developed by Sweldens. These filters are almost compact support and perfect reconstruction. By using TVLWF, we demonstrate an application to data compression of electrocardiogram (ECG) which is one of the semi-periodic time-series signals and show that the time-varying system can be constructed easily and the proposed method is very useful for data compression.

We have developed an InP-based monolithic optical frequency discriminator consisting of a temperature-insensitive optical filter and dual photodiodes. This integrated device detects the optical frequency deviation of the input light as differential photocurrent from the dual photodiodes, and the photocurrent is fedback to the light source for frequency stabilization through a differential amplifier. The FSR and extinction ratio of the filter are 50 GHz and 20 dB. The total opto-electronic conversion efficiency is 40%. In a frequency stabilization experiment using the developed discriminator, the frequency fluctuation of a DFB laser was reduced to less than 10 MHz.

A problem in image recognition in practical circumstances is that an observed image is often degraded by an imaging system. A conventional method in such a case is first to estimate the parameters of the imaging system and then restore the image before analysis. Here, we propose an alternative approach based on phase invariants in Fourier domain that needs no restoration and is fairly robust against both blur and noise. We show that the image phases in positive region of the Fourier transform of the point spread function (PSF) are blur-invariant provided that the PSF is central symmetric. Under the phase-invariant assumption, a phase correlation function between a standard image and the degraded image is used in developing the recognition algorithm. The effectiveness of this algorithm is demonstrated through experiments using ten classes of figure images from car license plates.

Petri net is a graphical and mathematical modeling tool for discrete event systems. This paper treats analysis problems of time Petri nets. In this model, a minimal and a maximal firing delays are assigned to each transition. If a transition is 'enabled' it can fire after minimal delay has passed and must fire before maximal delay has elapsed. Since time Petri net can simulate register machines, it has equivalent modeling power to that of Turing machine. It means, however, that most of the analysis problems of time Petri nets with general net structures are undecidable. In this paper, net structures are restricted to a subclass called partially ordered condition (POC) nets and dissynchronous choice (DC) nets. Firing delays are also restricted to satisfy 'static fair condition' which assures chance to fire for all transitions enabled simultaneously. First, a sufficient condition of liveness of time POC net with the static fair condition is derived. Then it is shown that liveness of time DC net with static fair condition is equivalent to liveness of the underlying nontime net. This means that liveness problem of this class is decidable. Lastly, liveness problem of extended free choice (EFC) net is shown to be decidable.

It is an important problem in signal processing, system realization and system identification to find linear discrete-time systems which are consistent with given covariance parameters. This problem is formulated as a problem of finding discrete-time positive real functions which interpolate given covariance parameters. Various investigations have yielded several significant solutions to the problem, while there remains an important open problem concerning the McMillan degree. In this paper, we use more general input-output characteristics than covariance parameters and consider finding discrete-time positive real matrix functions which interpolate such characteristics. The input-output characteristics are given by the coefficients of the Taylor series at some complex points in the open unit disk. Thus our problem is a generalization of the interpolation problem of covariance parameters. We reduce the problem to a directional interpolation problem with a constraint and develop the solution by a state-space based new approach. The main results consist of the necessary and sufficient condition for the existence of the discrete-time positive real matrix function which interpolates the given characteristics and has a limited McMillan degree, and a parameterization of all such functions. These are a contribution to the open problem and a generalization of the previous result.

In this paper, a new feature which is characterized by the extrema density of 2-D wavelet frames estimated at the output of the corresponding filter bank is proposed for texture segmentation. With and without feature selection, the discrimination ability of features based on pyramidal and tree-structured decompositions are comparatively studied using the extrema density, energy, and entropy as features, respectively. These comparisons are demonstrated with separable and non-separable wavelets. With the three-, four-, and five-category textured images from Brodatz album, it is observed that most performances with feature selection improve significantly than those without feature selection. In addition, the experimental results show that the extrema density-based measure performs best among the three types of features investigated. A Min-Min method based on genetic algorithms, which is a novel approach with the spatial separation criterion (SPC) as the evaluation function is presented to evaluate the segmentation performance of each subset of selected features. In this work, the SPC is defined as the Euclidean distance within class divided by the Euclidean distance between classes in the spatial domain. It is shown that with feature selection the tree-structured wavelet decomposition based on non-separable wavelet frames has better performances than the tree-structured wavelet decomposition based on separable wavelet frames and pyramidal decomposition based on separable and non-separable wavelet frames in the experiments. Finally, we compare to the segmentation results evaluated with the templates of the textured images and verify the effectiveness of the proposed criterion. Moreover, it is proved that the discriminatory characteristics of features do spread over all subbands from the feature selection vector.

This paper proposes and investigates the adaptive single-user receiver with co-channel interference (CCI) canceller based on orthogonalizing matched filter (OMF) using the multi-dimensional (multi-D) lattice filters for DS/CDMA in a multipath environment. A conventional single-user receiver using OMF cannot correctly cancel CCI in the presence of multipath in a channel, because the desired user's signal component and other users' intersymbol interference (ISI), due to multipath, still remain at the output of OMF, and then a correct replica of CCI cannot be generated. The proposed receiver can solve this problem because a multi-D IIR lattice filter can distinguish the desired user's signal component from the other users' ones and remove the ISI of all users' signals by Gram-Schmidt orthogonalization. And a multi-D FIR lattice filter can selectively regenerate undesired users' signal components which contain neither the desired user's signal component nor ISI. The proposed receiver based on multi-D lattice filters can apply orthogonality property of the OMF to not only a direct wave but also to delayed waves in a multipath channel. Since the proposed receiver does not have to know spreading codes of multiusers except the desired user, it will be applicable at a mobile terminal in the forward link in a multipath environment. Computer simulations show the proposed receiver have capability to cancel the CCI and converges fast in a multipath channel.

This paper presents a novel dead-beat synchronization scheme and applies it to communications in discrete-time chaotic systems. A well-known Henon system is considered as an illustrative example. In addition, a Henon-based image processing application effectively exploits the proposed scheme's effectiveness.

A nonlinear time series predictor was proposed, in which a nonlinear sub-predictor (NSP) and a linear sub-predictor (LSP) are combined in a cascade form. This model is called "hybrid predictor" here. The nonlinearity analysis method of the input time series was also proposed to estimate the network size. We have considered the nonlinear prediction problem as a pattern mapping one. A multi-layer neural network, which consists of sigmoidal hidden neurons and a single linear output neuron, has been employed as a nonlinear sub-predictor. Since the NSP includes nonlinear functions, it can predict the nonlinearity of the input time series. However, the prediction is not complete in some cases. Therefore, the NSP prediction error is further compensated for by employing a linear sub-predictor after the NSP. In this paper, the prediction mechanism and a role of the NSP and the LSP are theoretically and experimentally analyzed. The role of the NSP is to predict the nonlinear and some part of the linear property of the time series. The LSP works to predict the NSP prediction error. Furthermore, predictability of the hybrid predictor for noisy time series is investigated. The sigmoidal functions used in the NSP can suppress the noise effects by using their saturation regions. Computer simulations, using several kinds of nonlinear time series and other conventional predictor models, are demonstrated. The theoretical analysis of the predictor mechanism is confirmed through these simulations. Furthermore, predictability is improved by slightly expanding or shifting the input potential of the hidden neurons toward the saturation regions in the learning process.

Recently, Kundur and Hatzinakos showed that a linear restoration filter designed by using the almost obvious a priori knowledge on the original image, such as (i) nonnegativity of the true image and (ii) the smallest rectangle encompassing the original object, can realize a remarkable performance for a blind image deconvolution problem. In this paper, we propose a new set-theoretic blind image deconvolution scheme based on a recently developed convex projection technique called Hybrid Steepest Descent Method (HSDM), where some partial information can be utilized set-theoretically by parallel projections onto convex sets while the others are incorporated in a cost function to be minimized by a steepest descent method. Numerical comparisons with the standard set-theoretic scheme based on POCS illustrate the effectiveness of the proposed scheme.

In this paper we propose an algorithm for generating maximum weight independent sets in a circle graph, that is, for putting out all maximum weight independent sets one by one without duplication. The time complexity is O(n3 + β ), where n is the number of vertices, β output size, i. e. , the sum of the cardinalities of the output sets. It is shown that the same approach can be applied for spider graphs and for circular-arc overlap graphs.

In this paper, we propose a new structure of blind equalizer and its cost function. The proposed cost function is a quadratic form and has the unique solution. In addition, the proposed scheme can employ iterative algorithms which achieve less computational complexity and can be easily realized in real time processing. In order to verify the effectiveness of the proposed schemes, several computer simulations including a 64-QAM signal equalization have been shown.

We propose a new bit timing recovery (BTR) scheme, called perturbed sampling BTR (PSBTR), that can operate near the symbol rate in high-bit-rate wireless systems. A peculiar sample clock, the duty factor of which is not 50%, is used in the PSBTR scheme. We call this type of clock a perturbed sample clock and use it for clock recovery. In PSBTR, there is no cycle slip of the sample clock, and the PSBTR circuit is mostly digital. We examine the performance of the PSBTR scheme under additive white Gaussian noise (AWGN) by computer simulation and experiment, and from these results, clarify the relationship between the performance and circuit parameters of the PSBTR circuit. The overall results indicate that the PSBTR scheme performs well and can be employed as a BTR scheme for high-bit-rate wireless systems.