Two drawbacks of pyramidal wavelet transforms for finite-length sequences are the lack of conservation of the support and the boundary effect. In this letter, the structure of cyclic wavelet transforms (CWT) is used to permute the input and output data to map them into a linear array. Systolic realization of cyclic wavelet packet transforms (CWPT) is also presented to adequately deal with finite-length sequences which have dominant information on high or median frequency channels. The VLSI architectures designed in this letter are very attractive because adaptive processing can be achieved by just programming the filter coefficients.

The transform coding scheme is often used for data compression of images, but the blocking effects peculiar to the scheme appear more clearly in reproduced images as a coding rate (bits/pixel) decreases. These effects can sometimes be viewed as a periodical square-grid overlaying the images. In this paper,we propose a new method for selectively measuring the above blocking effects among several types of image degradation by means of the techniques of nonlinear signal processing for spectral infomation (cepstral techniques), in order to compare the amount of blocking effects for the different coding images. First a two-component model which consists of DC and AC images, is discussed from a viewpoint of subimage-by-subimage coding, and some basic properties of cepstral information for the model are investigated. Then we show a procedure to compute the cepstral information for two-dimensional image signals taking the horizontal and vertical directions ioto account, and introduce a cepstral mean square error (CMSE) as a new measure to estimate the amount of blocking effects. The computer simulation results for some test images using different coding schemes show that the amount of blocking effects in each image can be easily measured and estimated by this method even when the blocking effects appear slightly.

The medial axis transform (MAT) is an image representation scheme. For a binary image, the MAT is defined as a set of upright maximal squares which consist of pixels of value l entirely. The MAT plays an important role in image understanding. This paper presents a parallel algorithm for computing the MAT of an n n binary image. We show that the algorithm can be performed in O(log n) time using n2/log n processors on the EREW PRAM and in O(log log n) time using n2/log log n processors on the common CRCW PRAM. We also show that the algorithm can be performed in O(n2/p2 + n) time on a p p mesh and in O(n2/p2 + (n log p)/p) time on a p2 processor hypercube (for 1 p n). The algorithm is cost optimal on the PRAMs, on the mesh (for 1 p n) and on the hypercube (for 1 p n/log n).

This paper discusses a massively parallel interconnection scheme for multithreaded architecture and introduces a new class of direct interconnection networks called the hierarchical Multidimensional Directed Cycles Ensemble (hMDCE). Its suitability for massively parallel systems is discussed. The network is evolved from the Multidimensional Directed Cycles Ensemble (MDCE) network, where each node is substituted by lower-level sub-networks. The new network addresses some serious problems caused by the increasing scale of parallel systems, such as longer latency, limited throughput and high implementation cost. This paper first introduces the MDCE network and then presents and examines in detail the hierarchical MDCE network. Bisection bandwidth of hMDCE is considerably reduced from its ancestor MDCE and the network performs significantly higher throughput and lower latency under some practical implementation constraints. The gate count and delay time of the compiled circuit for the routing function are insignificant. These results reveal that the hMDCE network is an important candidate for massively parallel systems interconnection.

High-resolution algorithms for the detection and estimation of Directions Of Arrival (DOA) such as MUSIC, lead to accurate results but require the computation of the noise-subspace through an expensive covariance matrix eigendecomposition. Adaptive estimators of the noise-subspace can be very useful in a non-stationary environment when the convergence is possible with a few number of snapshots. Some adaptive methods are presented showing that an indirect noise-subspace estimation through a signal subspace estimation can be advantageous both in terms of convergence rate and computation complexity during each update. Some computer simulations examples showing performances are provided.

This paper first presents the performance analysis of the NACF algorithm. The results show the possibility of the degradation in the convergence speed. To improve the convergence speed, the bias term is introduced into the NACF algorithm and its efficiency is investigated through the computer simulations.

This paper introduces a new method to recover 3-D road plane from its 2-D monocular perspective image. The research is aimed at the reconstruction of depth information from the 2-D visual input in road following and navigation. Planar road model is considered and the road-centered coordinate system which forms slope and turn angles with camera-centered coordinate system is used to describe boundary points on road plane. We develop approaches to find matching points of boundaries of road and to obtain angular parameters thereafter. A way of finding depth of matching points from the perspective images and angular parameters together is proposed. Therefore the 3-D road reconstruction can be replicated without introducing any parameters of inverse perspective.

We proposed a new marker design for passive alignment of a laser to a fiber on a silicon waferboard. Our fiducial marker is simple form and easy to fabricate. With a unique marker design, high accurate positioning of the laser chip is easily achieved using a conventional flip-chip bonder. We have successfully fabricated laser modules with uniform coupling, within 1 dB for a flat end single-mode fiber and within 2 dB for a hemispherical end fiber. This assembly method offers the potential for low-cost optical module packaging.

During the last decade the decrease in the size of computing machinery, coupled with the increase in their computing power has lend to the development of the concept of mobile computing. Effects of this new vision is currently evident in the flourishing numbers of mobile telephones and portable computing units. In this paper we briefly investigate some issues concerning the security of mobile computing systems, within the framework of the categories of mobility, disconnection, data access modes and scale of operation (Imielinski & Badrinath, 1993). In contrast to previous works which concentrate on security in wireless communications, we focus on the security of interactions which are built upon the underlying wireless communications medium. Some conclusions are presented on the future directoins for security research in mobile computing sysytems.

Exploring enormous state graphs represented implicitly by ordered binary decision diagrams (OBDDs) is one of the most successful applications of OBDDs. However, our worst-case analysis of implicit graph representations by OBDDs shows that there are cases where OBDD representations are not optimal and require more space than adjacency lists. As an improvement, we propose a new type of BDDs, called Patricia BDDs, which are capable of implicit representation of graphs while their worst-case sizes are kept equal or less than adjacency lists and OBDDs.

In this paper, we present an exact analysis and an efficient matrix-analytic procedure to numerically evaluate the performance of cellular mobile networks with hand-off. In high-capacity micro-cell cellular radio communication networks, a cell boundary crossed by moving users can generate many hand-off attempts. This paper considers such a priority scheme that some channels and buffers are reserved for hand-off calls to reduce the forced termination of calls in progress. Performance characteristics we obtained include blocking probability, channel utilization, average queue length and average waiting time for hand-off calls. Using the matrix-analytic solution for the stationary state probability distribution, we also derive the probability distribution of the waiting time of a hand-off call. Numerical results show how priority can be provided to hand-off calls according to the number of reserved channels and buffer size. They also clarify the effect of the hand-off priority scheme on the standard deviation of waiting time of a hand-off call.

In this paper, we propose an analytic model using a semi-markov process for parallel computers which provides hardware support for a cache coherence mechanism. The model proposed here, the Semi-markov Memory and Cache coherence Interference model, can be used for the performance prediction of cache coherence based parallel computers since it can be easily applied to descriptions of the waiting states due to network contention or memory interference of both normal data accesses and cache coherence requests. Conventional analytic models using stochastic processes to describe parallel computers have the problem of numerical explosion in the number of states necessary as the system size increases even for simple parallel computers without cache coherence mechanisms. The number of states required by constructing our proposing analytic model, however, does not depend on the system size but only on the kind of cache coherence protocol. For example, the number of states for the Synapse cache coherence protocol is only 20, as is described in this paper. Using the proposed analytic model, we investigate several comparative experiments with widely known simulation results. We found that there is only a 7.08% difference between the simulation and our analytic model, while our analytic model can predict the performance of a 1,024 processor system in the order of microseconds.

Let W be a real symmetric matrix associated with a weighted 2-connected planar graph. It is important to study a fast algorithm to solve the linear system Wx = c, since the system has many various applicaions, for example to solve partial defferencial equations numerically. In this paper, a new algorithm for the solution of a linear system of equations by Δ-Y transformations is proposed, and a sufficient condition for using this algorithm is proved. We show that this algorithm solves in O (n3/2) time a linear system associated with a planar graph which is embedded a cylinder graph with n vertices.

In this paper, we show that by suitably selecting a notation to construct synchronization requirement specifications (SRS) for multimedia presentation we can express the timing characteristics at an abstract level, verify the specification, and obtain a hardware implementation through a sequence of transformations of the specification. First, we introduce the notion of a well-formed SRS and its hardware model. Second, we model an SRS as a timed Petri net and interpret the transitions of the net as hardware signals. To obtain logic functions from the SRS, we simplify the net and obtain a signal transition graph satisfying the unique state coding property. Finally, we show how to obtain a logic-level design of synchronizers.

This paper is concerned with spoken language translation in multimedia communication environment. We summarize the current research activities, by describing various spoken language translation systems and the multimodal technology related to spoken language translation. We propose a spoken language translation system that exploits the multimedia communication environment in order to overcome the limits caused by imperfect speech recognition. Our approach is in contrast to that of most conventional speech translation systems that limit their dialogue domains to obtain better speech recognition. We also propose a performance measure for spoken language translation systems. Our measure is defined as the ratio of the information quantities at each end of communication. Using this measure, we show that multimedia enhance spoken language translation systems.

This paper describes the results obtained of a prototype system, VeriProc/1, based on an algorithm we first presented in [13] which can prove the correctness of pipelined processors automatically without pipeline invariant, human interaction, or additional information. No timing relations such as an abstract function or β-relation is required. The only information required is to specify the location of the selectors in the design. The performance is independent of not only data width but also memory size. Detailed analysis of CPU time is presented. Further, don't-care forcing using additional data easily prepared by the user can improve performance.

We propose a speech recognition method using fusion of auditory and visual information for accurate speech recognition. Since we use both auditory information and visual information, we can perform speech recognition more accurately in comparison with the case of either auditory information or visual information. After processing each information by HMM, they are fused by linear combination with weight coefficient. We performed experiments and confirmed the validity of the proposed method.

In this paper, a super-resolution method based on the Discrete Cosine Transform (DCT) is proposed for a signal with some frequency damage. If the damage process can be modeled as linear convolutoin with a type 1 linear phase FIR filter, it is shown that some DCT coefficients of the damaged signal are the same as those of the original signal except for the DCT coefficients corresponding to the frequency damage. From this investigation, the proposed method is provided for the DCTs with four types as expanding the super-resolution method based on the Discrete Fourier Transform (DFT). In addition,two magnification approaches based on the proposed method are described to improve the conventional approach.

Neural network hardware using time-shared bus and integer representation architecture has already been fabricated and reported from the design viewpoint. However, nothing related to performance evaluation of hardware has yet been presented. Computation-speed, scalability and learning accuracy of hardware are evaluated theoretically and experimentally using a Back Propagation (BP) algorithm. In addition, a mirror-weight assignment technique is proposed for high-speed computation in the BP. NETTalk, an English-pronunciation-reasoning task, has been chosen as the target application for the BP. In the experiment, recently-developed neuro-hardware based on the above architecture and its parallel programming language are used. An outline of the language is described along with BP programming. Mirror-weight assignment allows maximum speed at 55.0 MCUPS (Million Connections Updated Per Second) using 256 neurons in the hidden-layer (numbers of neurons in input-and output-layers are fixed at 203 and 26 respectively in NETTalk). In addition, if scalability is defined as a function of the number of neurons in the hidden-layer, the machine retains high scalability at 0.5 if such a maximum speed needs to be used. No degradation in learning accuracy occurs when experimental results computed using the neuro-hardware are compared with those obtained by floating-point representation architecture (workstation). The experiment indicates that the present integer representational design of the neuro-hardware is sufficient for NETTalk. Performance has been evaluated theoretically. For evaluation purposes, it is assumed that most of the total execution-time is taken up by bus cycles. On the basis of this assumption, an analytical model of computation-speed and scalability is proposed. Analytical predictions agreed well with experimental results.

A method to correct the path-integrated attenuation derived from spaceborne radar measurement for the non-uniform beam filling (NUBF) effect is studied . A preliminary test using the data obtained from shipborne and ground-based radars is performed. It is found that the relation between the coarse-scale variability (radar-measurable quantity, σL) and the fine-scale variability (a quantity necessary for the NUBF correction, σH) of rain depends somewhat upon the rain cases studied and there still remains some underestimation in the corrected results. Nevertheless, the test result demonstrates the potential of utilizing the "local" statistical properties of rain in order to decrease the bias error in rain rate estimation caused by the NUBF.