This work is targeted to understand the operating principle of the feedback type echo canceller for use in an FM broadcasting receiver and to study its compensating features and the effects of the practical operating environment on its performance. The effects of the tap interval and the compensation performance in the presence of an echo with excess delay 0 - 15 µs are examined. The results show that the tap interval should be selected according to the observable bandwidth of the channel transfer function and the performance of a feedback type echo canceller has a wavelike curve with respect to the excess delay of the echo. To improve the performance of the feedback type echo canceller, an adaptive echo canceller operating with CM algorithm is proposed and examined with computer simulation. The results show that the compensation performance is improved.

This paper introduces an object-based distributed shared memory (DSM) system called Adsmith. The primary goal of Adsmith is to provide a low-cost, portable, and efficient DSM for networks of workstations (NOW). Adsmith achieves this goal by building on top of PVM, a widely supported communication subsystem, as a user-level library and by incorporating many traffic reduction and latency hiding techniques. Issues involved in the design of Adsmith and our solution strategies will be discussed. Preliminary performance evaluation of Adsmith on a network of Pentium computers will be presented. The results show that programs developed with Adsmith can achieve a performance comparable to that developed with PVM.

Several types of transmission-line coupling are analyzed to use in one- and two-dimensional active antenna arrays, and a method is developed to scan the beam of the arrays using the mutual locking theory. To compensate the undesired effect of strong radiative coupling of the nearest neighbor elements on the phased array performance, addition of resistive stubs to the end elements is proposed. In a 14 array it was observed that after the connection of resistive stubs, the scanning range of the array increased considerably. The effect of oscillator amplitudes on the phased array behavior is explored numerically. In the experiments main beam of 22 and 33 active antenna arrays were steered up to 25 and 15, respectively in the H-plane.

Recently, the spatio-temporal filter using linear analog Cellular Neural Network (CNN), called CNN filter array, has been proposed for the purpose of dynamic image processing. In this paper, we propose a design method of descrete-time cellular neural network filter which selectively extracts the particular moving object from other moving objects and noise. The CNN filter array forms a spatio-temporal filter by arranging cells with a same function. Each of these cells is a simple linear analog temporal filter whose input is the weighted sum of its neighborhood inputs and outputs and each cell corresponds to each pixel. The CNN filter is formed by new model of discrete time CNN, and the filter parameters are determined by applying backpropagation algorithm in place of the analytic method. Since the number of connections between neurons in the CNN-type filter is relatively few, the required computation in the learning phase is reasonable amount. Further, the output S/N ratio is improved by introducing nonlinear element. That is, if the ratio of output to imput is smaller than a certain value, the output signal is treated as a noise signal and ought to be rejected. Through some examples, it is shown that the target object is enhanced in the noisy environment.

Advanced scientific and engineering problems require massively parallel computing. Critical to the designand ultimately the performanceof such computing systems is the interconnection network binding the computing elements, just as is the cardiovascular network to the human body. This paper develops a new interconnection network, "Tori connected mESHes (TESH)," consisting of k-ary n-cube connection of supernodes that comprise meshes of lower level nodes. Its key features are the following: it is hierarchical, thus allowing exploitation of computation locality as well as easy expansion (up to a million processors), and it appears to be well suited for 3-D VLSI implementation, for it requires far fewer number of vertical wires than almost all known multi-computer networks. Presented in the paper are the architecture of the new network, node addressing and message routing, 3-D VLSI/ULSI considerations, and application of the network to massively parallel computing. Specifically, we discuss the mapping on to the network of stack filtering, a hardware oriented technique for order statistic image filtering.

In fully connected Multilayer perceptron (MLP), all the hidden units are activated by samples from the whole input space. For complex problems, due to interference and cross coupling of hidden units' activations, the network needs many hidden units to represent the problem and the error surface becomes highly non-linear. Searching for the minimum is then complex and computationally expensive, and simple gradient descent algorithms usually fail. We propose a network, where the input space is partitioned into local sub-regions. Subsequently, a number of smaller networks are simultaneously trained by overlapping subsets of the input samples. Remarkable improvement of training efficiency as well as generalization performance of this combined network are observed through various simulations.

Electroluminescent (EL) devices with mixed single layer that consist of fluorescent dyes, distylylbiphenyl derivative (DPVBi) and triphenylamine derivative (TPD), are studied. Blue light emission was observed from the device with DPVBi and TPD. White emission over 2,500 cd/m2 was observed from the devices with mixed single layer of DPVBi, TPD and dicyanomethylene derivative (DCM).

In this paper,a protocol-based modeling and simulation method of performance evaluation for heavy traffic and transient LAN is proposed. In the method a node on a LAN is modeled as a set of detailed communication protocol models. By parallel and event driven processing of the models, high accuracy and high time-resolution of evaluation of LAN behaviors can be obtained at multi-layer protocols. The LANs at computer education sites have highly loaded peaks, and it is very hard to design large scale educational LANs. Proposed method can be used to evaluate such cases of heavy traffic and transient LAN.

This paper describes a new multiple DmB1C (Differential m Binary 1 Complement insertion) /DmB1M (Differential m Binary with 1 Mark insertion) coding scheme for high-speed optical multiplex transmission. The coding scheme has the characteristics of small consecutive identical digits and a good balance between marks and spaces. Furthermore, it has also good synchronization characteristics and higher flexibility for extension to high capacity transmission than the conventional mB1C or DmB1M coding schemes. We describe a design methodology for a multiplex transmission system using the proposed coding scheme, and verify the characteristics of the proposed coding scheme using an experimental setup of a 2.8 Gbit/s serial optical interconnection circuit, which has 16 parallel 156 Mbit/s inputs. The coding scheme realizes transmission systems with simple analog circuit configuration, and small digital circuit complexity with wide dynamic range and good mark ratio tolerance.

We previously proposed a robust hybrid edge detector which relaxes the trade off between robustess against noise and accurate localization of the edges. This hybrid detector separates the tasks of localization and noise suppresion between two sub-detectors. In this paper, we present an extension to this hybrid detector to determine its optimal parameters, independently of the scene. This extension defines a probabilistic cost function using for criteria the probability of missing an edge buried in noise and the probability of detecting false edges. The optimization of this cost function allows the automatic selection of the parameters of the hybrid edge detector given the height of the minimum edge to be detected and the variance of the noise, σ2n. The results were applied to the 2D case and the performance of the adaptive hybrid detector was compared to other detectors.

An extension is made for a set of systems that have a quadratic Lyapunov function in common for the purpose of analysis and design. The nominal set of system matrices comprises stable symmetric matricies, which admit a hyperspherical Lyapunov function. Based on stability robustness results, sets of matrices are constructed so that they share the same Lyapunov function with the nominal ones.

The finite reconfigurability and local reconfigurability of graphs were proposed by Sha and Steiglitz [1], [2] in connection with a problem of on-line reconfiguraion of WSI networks for run-time faults. It is shown in [2] that a t-locally-reconfigurable graph for a 2-dimensional N-vertex array AN can be constructed from AN by adding O(N) vertices and edges. We show that Ω(N) vertices must be added to an N-vertex graph GN in order to construct a t-locally-reconfigurable graph for GN, which means that the number of added vertices for the above mentioned t-locally-reconfigurable graph for AN is optimal to within a constant factor. We also show that a t-finitely-reconfigurable graph for an N-vertex graph GN can be constructed from GN by adding t vertices and tN + t (t+1)/2 edges.

A new compression algorithm for fingerprint images is introduced. A modified wavelet packet scheme which uses a fixed decomposition structure, matched to the statistics of fingerprint images, is used. Based on statistical studies of the subbands, different compression techniques are chosen for different subbands. The decision is based on the effect of each subband on reconstructed image, taking into account the characteristics of the Human Visual System (HVS). A noise shaping bit allocation procedure which considers the HVS, is then used to assign the bit rate among subbands. Using Lattice Vector Quantization (LVQ), a new technique for determining the largest radius of the Lattice and its scaling factor is presented. The design is based on obtaining the smallest possible Expected Total Distortion (ETD) measure, using the given bit budget. At low bit rates, for the coefficients with high-frequency content, we propose the Positive-Negative Mean (PNM) algorithm to improve the resolution of the reconstructed image. Furthermore, for the coefficients with low-frequency content, a lossless predictive compression scheme is developed. The proposed algorithm results in a high compression ratio and a high reconstructed image quality with a low computational load compared to other available algorithms.

Mixed Quasi Newton simulation algorithm that is capable of calculating analog circuits containing mixed level of element models is presented. Conventional circuit simulators usually apply Newton method to solve nonlinear system equations resulted from circuit equations. At each Newton iteration step, it is necessary to reevaluate the Jacobian stamp of circuit elements. However, obtaining the Jacobian stamp of elements described by complex behavior models is a computationally expensive process. To reduce the number of Jacobian evaluations, we combine Newton method and Quasi-Newton method as a new updating scheme. The simulation results show that our algorithm can reduce the number of Jacobian evaluations and improve the simulation time, particularly when simulating circuits containing many behavior model elements.

This paper presents a generating method of LSP parameter sequences for speech synthesis by rule. In our method, neural networks are schemed to generate LSP parameter sequences of Vowel-Consonant-Vowel (VCV) units. The quality of synthesized speech by concatenation way of VCV units through table-look-up technique can not be improved so much owing to the distortion appearing on VCV units junction. In our method, the neural networks concatenate VCV units step by step with less distortion on VCV units junction, which synthesizes good quality speech.

In this paper, a systematic method which synthesizes the datapath of Application Specific Instruction Processor (ASIP) is proposed. The behavioral description of application is written in instruction code defined on abstract machine. We introduce register transfer graph (RTG) to represent instructions and synthesis constraint tree to select the combinations of synthesis constraints to explore design space along area and performance axis. The high performance is achieved by scheduling micro-operations of instruction in out-of-order. The practical datapath is synthesized by considering connection geometry as well as the maximum utilization of hardware resources. To reduce connection cost, data transfer paths are minimized by replacing an inefficient data transfer path with its bypass route. The feasibility of the proposed synthesis method is verified with several experimental instruction sequences.

This paper describes a method to distinguish phase noise and amplitude noise from total oscillator noise in circuit simulation, and derives general relationships between periodic time-varying transfer functions for oscillators and phase and amplitude noises.

Introducing a mathematical model of noise in stereo images, we propose a new criterion for intelligent statistical inference about the scene we are viewing by using the geometric information criterion (geometric AIC). Using synthetic and real-image experiments, we demonstrate that a robot can test whether or not the object is located very far away or the object is a planar surface without using any knowledge about the noise magnitude or any empirically adjustable thresholds.

High-speed display of 3-D objects in virtual reality environments is one of the currently important subjects. Shape simplification is considered an efficient method. This paper presents a method of hierarchical cube-based segmentation for shape simplification and multiresolution model construction. The relations among shape simplification, resolution and visual distance are derived firstly. The first level model is generated from scattered range data by cube-base segmentation with the first level cube size. Multiresolution models are then generated by re-sampling polygonal patch vertices of each former level model with hierarchical cube-based segmentation structure. The results show that the algorithm is efficient for constructing multiresolution models of free-form shape 3-D objects from scattered range data and high compression ratio can be obtained with little noticeable difference during the visualization.

In this paper, the evaluation of a hybrid acquisition performance has been considered for the pilot signal in direct sequence code division multiple access (DS/CDMA) forward link. The hybrid acquisition is introduced by the combination of two schemes, parallel and serial acquisitions. The mean acquisition time of the hybrid acquisition scheme is derived to consider both case 1 (the correct code-phase offsets ae included in one subset) and case 2 (the correct code-phase offsets exist at the boundary of two subsets), which are caused by the distribution of the correct code-phase offsets between two subsets. Detection, false alarm, and miss probabilities are derived for the cases of multiple correct code-phase offsets and multipath Rayleigh fading channel. Results are provided for the acquisition performance with respect to system design parameters such as postdetection integration length in the search and verification modes, subset size, and number of I/Q noncoherent correlators. Also, comparision between hybrid acquisition and parallel acquisition under the same hardware complexity is provided in terms of the minimum mean acquisition time.