In this paper we analize the performance of Trellis Coded Modulation (TCM) schemes with coherent detection operating in a frequency flat, mobile Rayleigh fading environment, and with different knowledge levels on both the amplitude and phase fading processes (the latter is not assumed as usual to be ideally tracked), or Channel State Information (CSI). For example, whereas ideal CSI means that both the amplitude and phase fading characteristics are perfectly known by the receiver, other situations that are treated consider perfect knowledge of the amplitude (or phase) with complete disregard of the phase (or amplitude), as well as non concern on any of them. Since these are extreme cases, intermediate situations can be also defined to get extended bounds based on Chernoff which allow the phase errors, in either form of constant phase shifts or randomly distributed phase jitter, to be included in the upper bounds attainable by transfer function methods, and are applicable to multiphase/level signaling schemes. We found that when both fading characteristics are considered, the availability of CSI enhances significatively the performance. Furthermore, for non constant envelope schemes with non ideal CSI and for constant envelope schemes with phase errors, an asymmetry property of the pairwise error probability is identified. Theoretical and simulation results are shown in support of the analysis.

This paper advocates the use of linear objective function in analytic analog placement. The role of linear and quadratic objctive functions in the behavior and results of an analog placement algorithm based on the force directed method is discussed. Experimental results for a MCNC benchmark circuit and another one from text books are shown to demonstrate the effect of a linear and a quadratic objective function on the analog constraint satisfaction and CPU time. By introducing linear objective function to the algorithm, we obtain better placements in terms of analog constraint satisfaction and computation cost than in case of conventional quadratic objective function.

This letter extends the Yule-Walker method to the estimation of ARMA parameters from output measurements corrupted by noise. In the proposed method it is assumed that the noise variance and the input are unknown. An algorithm for the estimation of noise variance is, therefore, given. The use of the variance estimation method proposed here together with the Yule-Walker equations allow the estimation of the parameters of a minimum phase ARMA model based only on noisy measurements of its output. Moreover, using this method it is not necessary to slove a set of nonlinear equations for MA parameter estimation as required in the conventional correlation based methods.

This paper proposes an approach for approximately realizing nonlinear mappings of interval vectors by interval neural networks. Interval neural networks in this paper are characterized by interval weights and interval biases. This means that the weights and biases are given by intervals instead of real numbers. First, an architecture of interval neural networks is proposed for dealing with interval input vectors. Interval neural networks with the proposed architecture map interval input vectors to interval output vectors by interval arithmetic. Some characteristic features of the nonlinear mappings realized by the interval neural networks are described. Next, a learning algorithm is derived. In the derived learning algorithm, training data are the pairs of interval input vectors and interval target vectors. Last, using a numerical example, the proposed approach is illustrated and compared with other approaches based on the standard back-propagation neural networks with real number weights.

In this paper, we develop a unified synthesizing approach for the cloning templates of Cellular Neural Networks (CNNs). In particular, we shall consider the case when the signal processing problem is complex, and a multilayered CNN with time-variant templates is necessary. The method originates from the existence of correspondence between the cloning templates of Cellular Neural Network and its discrete counterpart, Discrete-Time Cellular Neural Network (DTCNN), in solving a prescribed image processing problem when time-variant templates are involved. Thus, one can start with calculating the cloning templates from DTCNN, and then translating the cloning templates to those for CNN operations. As a result, the mathematical tools being used in the synthesis of Discrete-time Cellular Neural Network can also be applied to the analog type Cellular Neural Network. This inevitably helps to simplify the design problem of CNN for signal processing. Examples akin to contour drawing and parallel thinning are shown to illustrate the merits of our proposed method.

This paper proposes a new method to determine the shape of a surface by learning the mapping between three image irradiances observed under illumination from three lighting directions and the corresponding surface gradient. The method uses Phong reflectance function to describe specular reflectance. Lambertian reflectance is included as a special case. A neural network is constructed to estimate the values of reflectance parameters and the object surface gradient distribution under the assumption that the values of reflectance parameters are not known in advance. The method reconstructs the surface gradient distribution after determining the values of reflectance parameters of a test object using two step neural network which consists of one to extract two gradient parameters from three image irradiances and its inverse one. The effectiveness of this proposed neural network is confirmed by computer simulations and by experiment with a real object.

A network system is proposed for segmenting and extracting multiple moving objects in 2D images. The system uses an interconnected neural network in which grouping factors, such as edge proximity, smoothness of edge orientatio, and smoothness of velocity perpendicular to an edge, are embedded. The system groups edges so that the network energy may be minimized, i.e. edges may be organized into perceptually plausible configuration. Experimantal results are provided to indicate the performance and noise robustness of the system in extracting objects in synthetic images.

The mechanism for data retention failure of EPROM has been investigated by the Optical Beam Induced Current(OBIC) technique. It was found that the data of failure cells were changed from '1' to '0' during read-mode by laser irradiation by OBIC. The data in good cells was not changed. This result suggests the effective barrier height between Si and SiO2 is being lowered. In addition, the cross section technique revealed that gate electrode and gate oxide were exposed due to lack of dielectric layers. This defect seemed to be the cause of the barrier height lowering. The OBIC technique not only gives the failure location but a detailed information of the failure mechanism. We found that OBIC technique is a very powerful tool for the analysis of EPROM failure mechanisms. The usefulness of the Emission Micro Scope (EMS) technique is also discussed.

A novel pulse neural network model for sound localization has been proposed. Our model is based on the physiological auditory nervous system. Human beings can perceive the sound direction using inter-aural time difference (ILD) and inter-aural level difference (ILD) of two sounds. The model extracts these features using only pulse train information. The model is divided roughly into three sections: preprocessing for input signals; transforming continuous signals to pulse trains; and extracting features. The last section consists of two parts: ITD extractor and ILD extractor. Both extractors are implemented using a pulse neuron model. They have the same network structure, differing only in terms of parameters and arrangements of the pulse neuron model. The pulse neuron model receives pulse trains and outputs a pulse train. Because the pulses have only simple informations, their data structures are very simple and clear. Thus, a strict design is not required for the implementation of the model. These advantages are profitable for realizing this model by hardware. A computer simulation has demonstrated that time and level differences between two signals have been successfully extracted by the model.

The origin of and a method of enhancing the Optical Beam Induced Resistance Change (OBIRCH) signal for defect observation in VLSI metal interconnections is discussed based on a numerical analysis of three-dimensional thermal conduction and experimental results. The numerical analysis shows that the OBIRCH signal originates from a slight increase in the resistance of the metal line caused by laser beam heating and that its effect is influenced by the temperature of the metal layer. Both simulations and experimental results suggest that cooling the sample is preferable to detect the OBIRCH signal. The decrease in the total resistance of the metal line without any change in the amount of the resistance increase under laser illumination is found to be the main cause of the OBIRCH signal enhancement under low temperature measurement.

Graph parameters such as connectivity and diameter have been studied extensively due to their intrinsic importance in graph theory, combinatorics and their relations to (and applications in) fault tolerance and transmission delay in communications networks. The advent of VLSI technology and fiber optics material science has enabled us to design massively parallel processing computer systems and fast and complicated communications networks. All these systems increase their reliability by studying (among other) the existence of two (or more) disjoint paths connecting any two nodes. This paper addresses these issues by studying the width and length of containers in graphs and networks. In particular, the notions of w-distance and w-diameter on a graph are defined and studied which generalize both concepts of connectivity and diameter. Thses notions are also considered in finite groups. Other closely related parameters will be explored in the contexts of fault tolerance and routing. Known results are surveyed and open problems are offered for further investigation.

A method to improve the efficiency of dynamic fault imaging (DFI) by fully utilizing the CAD data in the CAD-linked electron beam test system is proposed. In the method, in order to shorten the long acquisition time of the stroboscopic voltage contrast images over the whole area of the chip during the entire test cycle, only the area and phase (time) required for fault tracing are selected by utilizing the CAD data. Furthermore, image processing techniques are combined with the method to improve the efficiency of the DFI. In particular, the signal averaging technique is used in order to improve the signal-to-noise ratio in the stroboscopic images where all voltage information data on the equipotential electrode recognized by the CAD layout data are averaged. This enables us to reduce the acquisition time of images. Moreover, the experimental system is set up so that the image processing can be performed in parallel with the acquisition of the stroboscopic images. The proposed method is applied to part of a 2k-transistor block of a nonpassivated CMOS LSI where a marginal fault is detected. The result shows that the method is an efficient approach to the fully automatic fault diagnosis in the CAD-linked electron beam test system. The proposed method could improve the efficiency of the conventional DFI by a factor of more than 1000.

We propose a large capacity broadband packet switch architecture using multiple optical star couplers and tunable devices whose tuning range is restricted. The proposed switch has the conventional three-stage switch structure. With the use of the generalized knockout principle and tunable lasers arranged in an appropriate manner, the switch becomes an output queueing system that yields the best possible delay/throughput performance. This switch requires minimal hardware at the cost of the increased number of wavelengths.

Thin (Ba0.75Sr0.25)TiO3 (BST) films to be used as dielectric materials in 256 Mbit DRAM capacitors were investigated. These films were deposited by an rf-sputtering method at substrate temperatures of 480 to 750. As substrate temperature increases, the dielectric constant to the films also increases, from 230 to 550. BST films prepared at temperatures higher than 700 show larger current leaks than films prepared at lower temperatures. A dielectric constant of 250, corresponding to a silicon oxide equivalent thickness (teq) of 0.47 nm, and a leak current density about 110-8 A/cm2 were obtained in 30-nm-thick film deposited at 660. Both of these values are sufficient for use in a 256 Mbit DRAM capacitor.

An automatic tracing algorithm of the transistor-level performance faults in the waveform-based approach with CAD-linked electron beam test system which utilizes a transistor-level circuit data in CAD database is proposed. Performance faults mean some performance measure such as the temporal parameters (rise time, fall time and so on) lies outside of the specified range in a VLSI. Problems on automatic fault tracing in the transistor level are modeled by using graphs. Combinational circuits which consist of MOS transistors are considered. A single fault is assumed to be in a circuit. The algorithm utilizes Depth-First Search algorithm where faulty upstream interconnections are searched as deeply as possible. Treatment of the faults on downstream interconnections and on unmeasurable interconnections is given. Application of this algorithm to the 2k-transistor block of a CMOS circuit showed its validity in the simulation.

As a generalization of the concept of pseudo-biorthogonal bases (PBOB), we already presented in Ref. [3] the theory of the so-called extended pseudo-biorthogonal bases (EPBOB). We introduce in this paper two special types of EPBOB called EPBOB's of type O and of type L. This paper discusses characterizations, construction methods, inherent properties, and mutual relations of these types of EPBOB.

The main problem in statistical pattern recognition is to design a classifier. Many researchers point out that a finite number of training samples causes the practical difficulties and constraints in designing a classifier. However, very little is known about the performance of a classifier in small training sample size situations. In this paper, we compare the classification performance of the well-known classifiers (k-NN, Parzen, Fisher's linear, Quadratic, Modified quadratic, Euclidean distance classifiers) when the number of training samples is small.

This paper investigates the properties of synchronized alternating one-way multicounter machines (lsamcm's) which operate in real time (lsamcm-real's) and whose leaf-sizes are bounded by a constant or some function of the length of an input. Leaf-size reflects the number of processors which run in parallel in scanning a given input. We first consider the hieracrchies of lsamcm-real's based on the number of counters and constant leaf-sizes. We next show that lsamcm-real's are less powerful than lsamcm's which operate in linear time when the leaf-sizes of these machines are bounded by a function L(n) such that limn[L(n) log n/n]0 and L(n)2.

Recently, efficient algorithms that exploit the separability of nonlinear mappings have been proposed for finding all solutions of piecewise-linear resistive circuits. In this letter, it is shown that these algorithms can be extended to circuits containing piecewise-linear resistors that are neither voltage nor current controlled. Using the parametric representation for these resistors, the circuits can be described by systems of nonlinear equations with separable mappings. This separability is effectively exploited in finding all solutions. A numerical example is given, and it is demonstrated that all solutions are computed very rapidly by the new algorithm.

For a discrete Lyapunov matrix equation, we present another such equation that shares the solution to the original one. This renders some existing lower bounds for measures of the size of the solution meaningful, when they yield only trivial bounds. A generalization of this result is suggested.