Diffraction pattern functions of an E-polarized scattering by a wedge composed of perfectly conducting metal and lossless dielectric with arbitrary permittivity are analyzed by applying an improved physical optics approximation and its correction. The correction terms are expressed into a complete expansion of the Neumann's series, of which coefficients are calculated numerically to satisfy the null-field condition in the complementary region.

The paper shows some of benefits of multi-unitary decomposition in signal analysis applications. It is emphasized that decompositions of complex discrete-time signals onto a single basis provide an incomplete and in such way potentially misleading image of the signals in signal analysis applications. It is shown that the multi-unitary decimated filter banks which decompose the analyzed signal onto several bases of the given vector space can serve as a tool which provides a more complete information about the signal and at the same time the filter banks can enjoy efficient polyphase component implementation of maximally decimated, i. e. nonredundant, filter banks. An insight into the multi-unitary signal decomposition is provided. It is shown that the multiple-bases representation leads to an efficient computation of frequency domain representations of signals on a dense not necessarily uniform frequency grid. It is also shown that the multiple-bases representation can be useful in the detection of tones in digital implementations of multifrequency signaling, and in receivers of chirp systems. A proof is provided that there are possible benefits of the multiple-bases representations in de-noising applications.

Indexing techniques usually are used in model-based object recognition and ray tracing algorithms. In this paper we present a new method for estimating the three-dimensional position of a subject (resp. object) in a circumscribed space based on an indexing method. We construct two and three-dimensional indices of a space, which are used to estimate the three-dimensional position by an interpolation technique. There are two processes in estimating the three-dimensional position of a subject (resp. object): preprocessing and three-dimensional position estimation. We have implemented this idea using stereo camera, and tested by using two different sizes of a grid pattern. Promising results for preprocessing and 3D position estimation are presented. Moreover, we show that this approach can also be extended for multiple cameras.

A procedure for radar target discrimination is presented in this paper. The scheme includes an enhancement of late-time noisy scattering data based on a proposed signal processing algorithm and a decision procedure using previously known resonance annihilation filters. The signal processing stage is specifically adapted to scattering signals and makes use of the results of the singularity expansion method. It is based on a signal reconstruction using the SVD of a data matrix with a suitable choice of the number of singular vectors employed. To justify the inclusion of this stage, this procedure is shown to maintain the signal characteristics necessary to identify the scattered response. Simulation results clearly reveal a significant improvement due to the inclusion of the proposed stage. This improvement becomes especially important when the noise level is high or the targets to be discriminated (five regular polygonal loops) have a similar geometry.

The complexity of designing communication protocols has lead researchers to develop various techniques for designing and verifying protocols. One of the most important techniques is a compositional technique. Using a compositional technique, a large and complex protocol is designed and verified by composing small and simple protocols which are easy to handle, design and verify. Unlike the other compositional approaches, we propose compositional techniques for simultaneously composing service specifications and protocol specifications based on Formal Description Techniques (FDTs) called LOTOS. The proposed techniques consider alternative, sequential, interrupt and parallel composition of service specifications and protocol specifications. The composite service specification and the composite protocol specification preserve the original behaviour and the correctness properties of individual service specifications and protocol specifications. We use the weak bisimulation equivalence (), to represent the correctness properties between the service specification and the protocol specification. When a protocol specification is weak bisimulation equivalent to a service specification, the protocol satisfies all the logical properties of a communication protocol as well as provides the services that are specified in the service specification.

Optical Code Division Multiple Access (OCD- MA) has been emerging as an attractive scheme in fiber optic communication systems as well as in space communication systems in past few years. In OCDMA systems, M-ary Pulse Position Modulation (PPM), has been regarded as an efficient signalling format which has the capability to reduce the channel interference caused by the other users and also to increase the number of simultaneous users. We apply error control coding to improve the system performance of pulse position modulated OCDMA (PPM/OCDMA) systems and this paper investigates the performance of M-ary PPM/OCDMA systems with M-ary convolutional coding. Dual-k code is used as the M-ary convolutional code and Optical Orthogonal Codes with the maximum cross correlation value of 1 and 2 are employed as the signature sequences. We derive an expression for the bit error probability of the new system and show that combining M-ary convolutional coding and M-ary PPM results in an improved error performance. Also it is shown that the number of simultaneous users can be significantly increased with the proposed system compared to the uncoded PPM/OCDMA system with the same bit error probability and with the same information bit rate. We also analyze the system with binary convolutional coding and a comparison with the proposed system is given.

This paper describes a new method for detecting the gaze position of a user on a monitor from monocular images. In order to detect the gaze position, we extract facial features (both eyes, nostrils and lip corners) automatically in 2D camera images and estimate the 3D depth information and the initial 3D positions of those features by recursive estimation algorithm in starting images. Then, when a user moves his/her head in order to gaze at one position on a monitor, the moved 3D positions of those features can be estimated from 3D motion estimation by Extended Kalman Filter (EKF) and affine transform. Finally, the gaze position on a monitor is calculated from the normal vector of the plane determined by those moved 3D positions of features. Especially, in order to obtain the exact 3D depth and positions of initial feature points, we unify three coordinate systems (face, monitor and camera coordinate system) based on perspective transformation. As experimental results, the 3D depth and the position estimation error of initial feature points, which is the RMS error between the estimated initial 3D feature positions and the real positions (measured by 3D position tracker sensor) is about 1.28 cm (0.75 cm in X axis, 0.85 cm in Y axis, 0.6 cm in Z axis) and the 3D motion estimation errors of feature points by Extended Kalman Filter (EKF) are about 3.6 degrees and 1.4 cm in rotation and translation, respectively. From that, we can obtain the gaze position on a monitor (17 inches) and the gaze position accuracy between the calculated positions and the real ones is about 2.1 inches of RMS error.

In this paper, we study a new hybrid speech coder which employs a modified version of the harmonic sinusoidal analysis to encode the periodic contents of speech waveform and to split the speech spectrum into two frequency regions of harmonic and random components. A reliable fundamental frequency is estimated for the harmonic region using both speech and its linear predictive (LP) residual spectrum. The peak envelope of speech spectrum is encoded in terms of the coefficients of an all-pole spectrum. A harmonic tracking algorithm appropriately interpolates the sinusoidal parameters to achieve a smooth transition between the parameter update points and to reconstruct an essential level of periodicity in the synthetic voiced speech. The random part of spectrum and unvoiced speech are coded using the conventional CELP algorithm. The individual components are then combined at the decoder to obtain the synthetic speech. The proposed hybrid coder which combines the powerful features of the sinusoidal and CELP coding algorithms yeilds a high quality synthetic speech at 4.05 kbps.

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.

This study is aimed to explore a fast convergence method of blind equalization using higher order statistics (cumulants). The efforts are focused on deriving new theoretical solutions for blind equalizers rather than investigating practical algorithms. Under the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i. e. the lag coefficients of the equalizer can be obtained from the eigenvectors of a higher order statistics matrix. A method of blind phase recovery is also proposed for QAM systems. Computer simulations show that very fast convergence can be achieved based on the approach.

In this paper, a general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived and implemented with simplified probabilistic models. The formula is the generalized probabilistic diffusion equation based on Bayesian model, and can be implemented into some different forms corresponding to the probabilistic models in the disparity neighborhood system or configuration. The probabilistic models are independence and similarity among the neighboring disparities in the configuration. The independence probabilistic model guarantees the discontinuity at the object boundary region, and the similarity model does the continuity or the high correlation of the disparity distribution. According to the experimental results, the proposed algorithm had good estimation performance. This result showes that the derived formula generalizes the probabilistic diffusion based on Bayesian MAP algorithm for disparity estimation. Also, the proposed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to O(n()) from O(n()4) of the generalized formula.

Equipment simulation can provide valuable support in reactor design and process optimization. This article describes the physical and chemical models used in this technique and the current state of the art of the available software tools is reviewed. Moreover, the potential of equipment simulation will be highlighted by means of three recent examples from advanced quarter micron silicon process development. These include a vertical batch reactor for LPCVD of arsenic doped silicon oxide, a multi station tungsten CVD reactor, and a plasma reactor for silicon etching.

In this paper, we consider the working VP and backup VP routing problems jointly and employ the integer programming based approach to maximize the system resource utilization and the network survivability. The VP planning problem is formulated as a nonlinear combinatorial optimization problem. The objective function minimizes the resource usage while maximizing the network survivability. By proper transformation of the objective function and applying cutting plane method, the original formulation is transformed into an integer linear programing formulation which is suitable for applying Lagrangian relaxation techniques. After Lagrangian relaxation, the problem is further decomposed into several tractable subproblems. Unlike others' work, the candidate path set does not need to be prepared in advance and the best paths are generated while solving subproblems in our approach. Heuristic algorithms based on the solving procedure of the Lagrangian relaxation are developed. Closely examining the gap between the heuristic upper bounds and the Lagrangian lower bounds reveals that the proposed algorithm can efficiently provide a nearly optimal solution for the survivable VP layout design in ATM networks.

Based on a previous work on handwritten Japanese kanji character recognition, a postprocessing system for handwritten Japanese address recognition is proposed. Basically, the recognition system is composed of CombNET-II, a general-purpose large-scale character recognizer and MMVA, a modified majority voting system. Beginning with a set of character candidates, produced by a character recognizer for each character that composes the input word and a lexicon, an interpretation to the input word is generated. MMVA is used in the postprocessing stage to select the interpretation that accumulates the highest score. In the case of more than one possible interpretation, the Conflict Analyzing System calls the character recognizer again to generate scores for each character that composes each interpretation to determine the final output word. The proposed word recognition system was tested with 2 sets of handwritten Japanese city names, and recognition rates higher than 99% were achieved, demonstrating the effectiveness of the method.

A new low voltage high-speed CMOS composite transistor is presented. It lowers supply voltage down to |Vt|+2 Vds,sat and considerably extends input voltage operating range and achieves high speed operation. As an application example, it is used in the design of a high-speed four quadrant analog multiplier. Simulations results using MOSIS 2µm N-well process with a 3 V supply are given.

We present a receiver structure with joint blind equalization, carrier recovery, and timing recovery. The blind equalizer employs a decomposition transversal filtering technique which can reduce the complexity of convolution to about a half. We analyze the performance surface of the equalizer cost function and show that the global minima correspond to perfect equalization. We also derive proper initial tap settings of the equalizer for convergence to the global minima. We describe the timing recovery and the carrier recovery methods employed. And we describe a startup sequence to bring the receiver into full operation. The adaptation algorithms for equalization, carrier recovery, and timing recovery are relatively independent, resulting in good operational stability of the overall receiver. Some simulation results for cable-modem type of transmission are presented.

Decision trees are used as a convenient means to explain given positive examples and negative examples, which is a form of data mining and knowledge discovery. Standard methods such as ID3 may provide non-monotonic decision trees in the sense that data with larger values in all attributes are sometimes classified into a class with a smaller output value. (In the case of binary data, this is equivalent to saying that the discriminant Boolean function that the decision tree represents is not positive. ) A motivation of this study comes from an observation that real world data are often positive, and in such cases it is natural to build decision trees which represent positive (i. e. , monotone) discriminant functions. For this, we propose how to modify the existing procedures such as ID3, so that the resulting decision tree represents a positive discriminant function. In this procedure, we add some new data to recover the positivity of data, which the original data had but was lost in the process of decomposing data sets by such methods as ID3. To compare the performance of our method with existing methods, we test (1) positive data, which are randomly generated from a hidden positive Boolean function after adding dummy attributes, and (2) breast cancer data as an example of the real-world data. The experimental results on (1) tell that, although the sizes of positive decision trees are relatively larger than those without positivity assumption, positive decision trees exhibit higher accuracy and tend to choose correct attributes, on which the hidden positive Boolean function is defined. For the breast cancer data set, we also observe a similar tendency; i. e. , positive decision trees are larger but give higher accuracy.

Three multiplicative algorithms for the floating-point divide operation are compared: the Newton-Raphson method, Goldschmidt's algorithm, and a naive method that simply calculates a form of the Taylor series expansion of a reciprocal. The series also provides a theoretical basis for Goldschmidt's algorithm. It is well known that, of the Newton-Raphson method and Goldschmidt's algorithm, the former is the more accurate while the latter is the faster on a pipelined unit. However, little is reported about the naive method. In this report, we analyze the speed and accuracy of each method and present the results of numerical tests, which we conducted to confirm the validity of the accuracy analysis. Basically, the comparison are made in the context of software implementation (e. g. , a macro library) and compliance with the IEEE Standard 754 rounding is not considered. It is shown that the naive method is useful in a realistic setting where the number of iterations is small and the method is implemented on a pipelined floating-point unit with a multiply-accumulate configuration. In such a situation, the naive method gives a more accurate result with a slightly lower latency, as compared with Goldschmidt's algorithm, and is much faster than but slightly inferior in accuracy to the Newton-Raphson method.

This paper presents a new efficient method for finding an "optimal" bi-decomposition form of a logic function. A bi-decomposition form of a logic function is the form: f(X) = α(g1(X1), g2(X2)). We call a bi-decomposition form optimal when the total number of variables in X1 and X2 is the smallest among all bi-decomposition forms of f. This meaning of optimal is adequate especially for the synthesis of LUT (Look-Up Table) networks where the number of function inputs is important for the implementation. In our method, we consider only two bi-decomposition forms; (g1 g2) and (g1 g2). We can easily find all the other types of bi-decomposition forms from the above two decomposition forms. Our method efficiently finds one of the existing optimal bi-decomposition forms based on a branch-and-bound algorithm. Moreover, our method can also decompose incompletely specified functions. Experimental results show that we can construct better networks by using optimal bi-decompositions than by using conventional decompositions.

Simple disjunctive decomposition is a special case of logic function decompositions, where variables are divided into two disjoint sets and there is only one newly introduced variable. It offers an optimal structure for a single-output function. This paper presents two techniques that enable us to apply simple disjunctive decompositions with little overhead. Firstly, we propose a method to find symple disjunctive decomposition forms efficiently by limiting decomposition types to be found to two: a decomposition where the bound set is a set of symmetric variables and a decomposition where the output function is a 2-input function. Secondly, we propose an algorithm that constructs a new logic representation for a simple disjunctive decomposition just by assigning constant values to variables in the original representation. The algorithm enables us to apply the decomposition with keeping good structures of the original representation. We performed experiments for decomposing functions and confirmed the efficiency of our method. We also performed experiments for restructuring fanout free cones of multi-level logic circuits, and obtained better results than when not restructuring them.