The paper obtains an algorithm to estimate the irregular sampling in wavelet subspaces. Compared to our former work on the problem, the new estimate is relaxed for some wavelet subspaces.

A constant modulus adaptive array algorithm is derived using analysis and synthesis filter banks to permit adaptive digital beamforming for wideband signals. The properties of the CMA adaptive array using the filter banks are investigated. This array would be used to realize adaptive digital beamforming when this is difficult by means of ordinary (that is, non-subband) processing due to the limited speed of signal processor operations. As an actual application, we present a beamspace adaptive array structure that combines the analysis and synthesis filter banks with RF-domain multibeam array antennas, such as those utilizing optical signal processing.

Recently, a great deal of effort has been devoted to the design problem of "constrained least squares M-D FIR filter" because a significant improvement of the squared error is expected by a slight relaxation of the minimax error condition. Unfortunately, no design method has been reported, which has some theoretical guarantee of the convergence to the optimal solution. In this paper, we propose a class of novel design methods of "constrained least squares M-D FIR filter. " The most remarkable feature is that all of the proposed methods have theoretical guarantees of convergences to the unique optimal solution under any consistent set of prescribed maximal error conditions. The proposed methods are based on "convex projection techniques" that computes the metric projection onto the intersection of multiple closed convex sets in real Hilbert space. Moreover, some of the proposed methods can still be applied even for the problem with any inconsistent set of maximal error conditions. These lead to the unique optimal solution over the set of all filters that attain the least sum of squared distances to all constraint sets.

On wide area networks (WANs), UDP has likely been used for real-time applications, such as video and audio. UDP supplies minimized transmission delay by omitting the connection setup process, flow control, and retransmission. Meanwhile, more than 80 percent of the WAN resources are occupied by Transmission Control Protocol (TCP) traffic. As opposed to UDP's simplicity, TCP adopts a unique flow control mechanism with sliding windows. Hence, the quality of service (QoS) of real-time applications using UDP is affected by TCP traffic and its flow control mechanism whenever TCP and UDP share a bottleneck node. In this paper, the characteristics of UDP packet loss are investigated through simulations of WANs conveying UDP and TCP traffic simultaneously. In particular, the effects of TCP flow control on the packet loss of real-time audio are examined to discover how real-time audio should be transmitted with the minimum packet loss, while it is competing with TCP traffic for the bandwidth. The result obtained was that UDP packet loss occurs more often and successively when the congestion windows of TCP connections are synchronized. Especially in this case, the best performance of real-time audio applications can be obtained when they send-small sized packets without reducing their transmission rates.

In this paper, we present a hierarchical technique for simultaneous pin assignment and global routing during floorplanning based on the minimum cost maximum integer flow algorithm with several heuristic cost functions. Furthermore, our algorithm handles feedthrough pins and equi-potential pins taking into account global routes. Our algorithm allows various user specified constraints such as pre-specified pin positions, wiring paths, wiring widths and critical nets. Experimental results including Xerox floorplanning benchmark have shown the effectiveness of the heuristics.

We show that characteristic functions of elements of self-similar tilings can be used as scaling functions of multiresolution analysis of L2(Rn). This multiresolution analysis is a generalization of a self-affine tiling multiresolution analysis using a characteristic function of element of self-affine tiling as a scaling function. We give a method of constructing a wavelet basis which realizes such an MRA.

We introduce an image contour clustering method based on a multiscale image representation and its application to image compression. Multiscale gradient planes are obtained from the mean squared sum of 2D wavelet transform of an image. The decay on the multiscale gradient planes across scales depends on the Lipshitz exponent. Since the Lipshitz exponent indicates the spatial differentiability of an image, the multiscale gradient planes represent smoothness or sharpness around edges on image contours. We apply vector quatization to the multiscale gradient planes at contours, and cluster the contours in terms of represntative vectors in VQ. Since the multiscale gradient planes indicate the Lipshitz exponents, the image contours are clustered according to its gradients and Lipshitz exponents. Moreover, we present an image recovery algorithm to the multiscale gradient planes, and we achieve the skech-based image compression by the vector quantization on the multiscale gradient planes.

Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.

Adaptive estimation of nonstationary sinusoidal signals or quasi-periodic signals in additive noise is of essential importance in many diverse engineering fields, such as communications, biomedical engineering, power systems, pitch detection in transcription and so forth. So far, Kalman filtering based techniques, recursive least square (RLS), simplified RLS (SRLS) and LMS algorithms, for examples, have been developed for this purpose. This work presents in detail a performance analysis for the SRLS algorithm proposed recently in the literature, which is used to estimate an enhanced sinusoid. Its dynamic and tracking properties, noise and lag misadjustments are developed and discussed. It is found that the SRLS estimator is biased, and its misadjustments are functions of not only the noise variance but also, unpleasantly, of the signal parameters. Simulations demonstrate the validity of the analysis. Application of the SRLS to a real-life piano sound is also given to peek at its effectiveness.

This paper describes recent standardization activities on optical networking and relevant issues which are conducted in ITU-T. The organization is first described, then, several recommendations both which are already recommended and expected to be completed in a couple of years.

Secret sharing schemes are good for protecting the important secrets. They are, however, inefficient if the secret shadow held by the shadowholder cannot be reused after recovering the shared secret. Traditionally, the (t, n) secret sharing scheme can be used only once, where t is the threshold value and n is the number of participants. To improve the efficiency, we propose an efficient dynamic secret sharing scheme. In the new scheme, each shadowholder holds a secret key and the corresponding public key. The secret shadow is constructed from the secret key in our scheme, while in previously proposed secret sharing schemes the secret key is the shadow. In addition, the shadow is not constructed by the shadowholder unless it is necessary, and no secure delivery channel is needed. Morever, this paper will further discuss how to change the shared secret, the threshold policy and cheater detection. Therefore, this scheme provides an efficient way to maintain important secrets.

The Multiwavelength Optical Networking (MONET) program consists of a consortium of industrial partners, working together with the intent to demonstrate the key capabilities needed for configurable WDM networks. This involves integrating WDM technologies with optical switching technologies to provide a managed, high capacity, national scale WDM server layer to transport optical signals transparently across multiple interworking subnetworks.

In this paper, we propose a new approach for describing image patterns. We integrate the concepts of multiscale image analysis, aura matrix (Gibbs random fields and cooccurrences related statistical model of texture analysis) to define image features, and to obtain the features having robustness with illumination variations and shading effects, we analyse images based on the Topographic Structure described by the Surface-Shape Operator, which describe gray-level image patterns in terms of 3D shapes instead of intensity values. Then, we illustrate usefulness of the proposed features with texture classifications. Results show that the proposed features extracted from multiscale images work much better than those from a single scale image, and confirm that the proposed features have robustness with illumination and shading variations. By comparisons with the MRSAR (Multiresolution Simultaneous Autoregressive) features using Mahalanobis distance and Euclidean distance, the proposed multiscale features give better performances for classifying the entire Brodatz textures: 112 categories, 2016 samples having various brightness in each category.

Recent progress in neural network research has demonstrated the usefulness of neural networks in a variety of areas. In this work, its application in the spatial resolution improvement of a remotely sensed low resolution thermal infrared image using high spatial resolution of visible and near-infrared images from Landsat TM sensor is described. The same work is done by an algebraic method. The tests developed are explained and examples of the results obtained in each test are shown and compared with each other. The error analysis is also carried out. Future improvements of these methods are evaluated.

The temperature dependence of central wavelength of optical filters is a serious problem for the dense WDM systems. This dependence is owing to the temperature dependence of optical path-length of the waveguide. In this study, we realized a temperature independent silica-based optical filter at 1. 55 µm wavelength using an athermal waveguide, in which optical pathlength is independent of temperature. First, we designed a silica-based athermal waveguide, and next we designed and fabricated a ring resonator using the athermal waveguide. As a result, we successfully decreased the temperature dependence of central wavelength to less than 4 10 -4 nm/K, which is 3% and 0. 3% of corresponding values of conventional silica-based and semiconductor waveguide filters, respectively.

Optical networking is likely to result in substantial cost savings in future telecommunications networks. The scalability and design flexibility of these networks are critical features which may influence the nature of future networking products. In this paper, we experimentally investigate networking technologies for optically time division multiplexed systems. We demonstrate significant advantages in terms of scalability, design flexibility and technology interoperability over the traditional wavelength division multiplexing approach.

Different-wavelength distributed feedback laser diodes with integrated modulators (DFB/MODs) are fabricated on a single wafer operate at wavelengths from 1. 52 µm to 1. 59 µm, a range comparable to the expanded Er-doped fiber amplifier gain band. A newly developed field-size-variation electron-beam lithography enables grating pitch to be controlled to within 0. 0012 nm, and narrow-stripe selective metal-organic vapor-phase epitaxy is used to control the bandgap wavelength of laser active layers and modulator absorption layers for each channel. The channel spacing of fabricated 40-channel DFB/MODs is 214 GHz in average with a standard deviation of 0. 39 nm. Very uniform lasing and modulating performances are achieved, such as threshold currents about 10 mA and extinction ratios about 20 dB at -2 V in average. These devices have been used to demonstrate 2. 5-Gb/s transmission over 600 km of a normal fiber with a power penalty of less than 1 dB.

Evaluating analytically computer architecture performance is mostly cheap and quick. However, existing analytical performance evaluation techniques usually have a difficult and time-consuming modeling process. Moreover, existing techniques do not support well the capability for finding the bottleneck and its cause of a target system being evaluated. To address the above problems and to enhance analytical performance evaluation technology, in this paper we propose a software tool that accepts system models described in a specification language, generating an executable program that performs the actual performance evaluation. The whole approach is built on a subsystem-oriented performance evaluation tool, which is, in turn, based on a formal subsystem-oriented performance evaluation technique and a subsystem specification language.

The new technique for reducing the load latency is presented. This technique, named tunneling-load, utilizes the register specifier buffer in order to reduce the load latency without fetching the data cache speculatively, and thus eliminates the drawback of any load address prediction techniques. As a consequence of the trend toward increasing clock frequency, the internal cache is no longer able to fill the speed gap between the processor and the external memory, and the data cache latency degrades the processor performance. In order to hide this latency, several techniques predicting the load address have been proposed. These techniques carry out the speculative data cache fetching, which causes the explosion of the memory traffic and the pollution of the data cache. The tunneling-load solves these problems. We have evaluated the effects of the tunneling-load, and found that in an in-order-issue superscalar platform the instruction level parallelism is increased by approximately 10%.

The Heart Rate Variability (HRV) analysis has become vigorous these days. One reason for this is that the HRV analysis investigates the dynamics of the autonomic nervous system activities which control the HRV. The Integral Pulse Frequency Modulation (IPFM) model is a pulse generating mechanism model in the nervous system, that is one of the models which connects the HRV to the autonomic nervous system activities. The IPFM model is a single frequency component model; however, the real HRV has multiple frequency components. Moreover, there are refractory periods after generating action potentials are initiated. Nevertheless, the IPFM model does not consider refractory periods. In order to make sure of the accuracy and the effectiveness of the integral function (IF) method applied to the real data, we consider the absolute refractory periods and two frequency components. In this investigation, the simulated HRV was made with a single and double frequency component using the IPFM model with and without absolute refractory periods. The original generating function of the IPFM model was demodulated by using the instantaneous heart rate tachogram. The power of the instantaneous pulse rate per minute was analyzed by the direct FFT method, the IF FFT method without the absolute refractory periods, and the IF FFT method with the absolute refractory periods. It was concluded that the IF FFT method can demodulate the original generating function accurately.