In this paper, we analyze a photodetection process of new kind theoretically, which transforms a coherent state of light so as to lead to nonstandard property, namely, sub-Poissonian distribution of its output photoelectron during its photodetection process. The properties of the photoelectron distribution are studied used as preamplifiers of both direct-detection and homodyne detection cases.

The mode partition noise of 1.3µm distributed feedback laser diodes (DFB LD's), which is induced by the externally reflected light, is studied experimentally and numerically. The mode partition noise is evaluated by the k-value. It is observed that the mode parition noise monotonically increases with the DC bias current when the reflected light affects DFB LD's and the DC bias current is above the threshold current. From the dependence of the k-value on the external power reflection coefficient, it is observed that the k-value dramatically increases when the external power reflection coefficient is above a value which differs from LD to LD. This is closely related to the fact that the tolerance to the externally reflected light depends on the threshold gain difference between the main mode and the dominant side mode.

In this paper, a new M-estimation technique for the linear prediction analysis of speech is proposed. Since in the conventional linear prediction (CLP) method the obtained estimates are very much affected by the large amplitude residual parts, in the proposed method we use a loss function which assigns large weighting factor for small amplitude residuals and small weighting factor for large amplitude residuals which is for instance caused by the pitch excitations. The loss function is based on the assumption that the residual signal has an independent and identical t-distribution t(α) with α degrees of freedom. The efficiency of this new estimator depends on α. When α=, we get the CLP method. When the proposed method with small α is applied to the problems of estimating the formant frequencies and bandwidths of the synthetic speech by finding the roots of the prediction polynomial, we can achieve a more accurate and a smaller standard deviation (SD) estimate than that with large α. When the signal is very spiky, the proposed method can ahieve more efficient and accurate estimates than that with robust linear prediction (RBLP) method. The loss function is modified in the similar manner as the autocorrelation method. The solution is calculated by the Newton-Raphson iteration technique. The simulation results show that only few iterations are needed to reach a stationary point, the stationary point is always a local minimum and the obtained prediction filter is always minimum phase. Preliminary experiments on the human speech data indicate that the obtained results are insensitive to the placement of the analysis window and a higher spectral resolution than the CLP and RBLP method can be achieved.

A specification formalism for business application software is presented. Our approach is to investigate specification documents which are actually used in development projects of business applications in banking, insurance, and government systems. Since the specification documents are prepared mainly for users' review for the developing software, the representation of the documents is designed to be easy to understand for users, only in business terminology without losing a certain level of formality. Also, to avoid redundancy of the specification, there are some implicit assumptions in the specification. We have analyzed some commonality of these assumptions hidden in specification documents and are trying to construct a language by formalizing the underlying system model.

After the intrinsic pulsed light illumination, a transient negative photoconductivity (TRANP) was observed in silicon doped with gold. The ambient temperature dependence of the TRANP-current was measured and compared with the simulated results obtained by solving rate equations. The temperature dependence of the peak value of the TRANP-current was in agreement with the simulated result. The activation energy of gold acceptor level obtained from the time constant in the recovery process was also consistent with the simulation. It was cleared from this result that the recovery process is dominated by the electron re-emission from gold acceptor level to the conduction band. It was concluded that the occurrence of the TRANP is well explained by using our model proposed before.

We will introduce W-trees of a W-graph which is a graph containing wild components. A wild component is an incompletely defined subgraph which is known to be a tree but what kind of the tree is unspecified. W-tree is defined as a set of edges and vertices of wild components obtained from a non-sigular major submatrix of a W-incidence matrix. The properties of a W-tree are useful for studying linear independent W-cutsets and so on in a W-graph.

In this letter, a generalized syndrome polynomial is proposed from which several decoding key-equations for Reed-Solomon codes can be derived systematically. These equations are always solved by the extended Euclidean algorithm.

The inherent simplicity of the LMS (Least Mean Square) Algorithm has lead to its wide usage. However, it is well known that high speed convergence and low final misadjustment cannot be realized simultaneously by the conventional LMS method. To overcome this trade-off problem, a new adaptive algorithm using Multiple ADF's (Adaptive Digital Filters) is proposed. The proposed algorithm modifies coefficients using multiple gradient vectors of the squared error, which are computed at different points on the performance surface. First, the proposed algorithm using 2 ADF's is discussed. Simulation results show that both high speed convergence and low final misadjustment can be realized. The computation time of this proposed algorithm is nearly as much as that of LMS if parallel processing techniques are used. Moreover, the proposed algorithm using more than 2 ADF's is discussed. It is understood that if more than 2 ADF's are used, further improvement in the convergence speed in not realized, but a reduction of the final misadjustment and an improvement in the stability are realized. Finally, a method which can improve the convergence property in the presence of correlated input is discussed. It is indicated that using priori knowledge and matrix transformation, the convergence property is quite improved even when a strongly correlated signal input is applied.

The authors design a simple feed system for a planar slotted waveguide array. A waveguide π-junction with negligible reflection is cascaded to compose a multiple-way power divider. The frequency characteristics of the power divided to each port and the reflection at the feed point are discussed and high performances are predicted. The maximum number of cascaded junctions in this system can be determined in terms of a desired frequency bandwidth and allowable deviation in divided power.

A formula for the variations in vertex-potentials caused by an increase of an edge-weight is derived using topological methods. This formula can be expressed in terms of the increase of the weight and the potential differences between two vertices joined by the edge with respect to three ordered vertex-pairs in the original network before the weight is increased.

We introduce a novel neural network called the T-Model and investigates the learning ability of the T-Model neural network. A learning algorithm based on the least mean square (LMS) algorithm is used to train the T-Model and produces a very good result for the T-Model network. We present simulation results on several practical problems to illustrate the efficiency of the learning techniques. As a result, the T-Model network learns successfully, but the Hopfield model fails to and the T-Model learns much more effectively and more quickly than a multi-layer network.

The introduction of Integrated Services Digital Networks (ISDNs) poses a variety of new questions on telecommunications network design and planning. Furthermore, the formulation of traditional network design and planning problems need to be revisited in the ISDN context. This paper presents an overview of the recent progress and new challenges in developing ISDN design and planning methodologies that exploit revolutionary new telecommunications technologies. It will cover some important issues for ISDN design and planning, and will concentrate on three issues that are of particular importance: Design of networks with digital information transfer capabilities, design of networks with advanced network/traffic control techniques, and use of reliability objectives for network design and planning.

Based on the Fornasini-Marchesini second model, an efficient algorithm is developed to derive the characteristic polynomial and the inverse of the system matrix from the state-space parameters. As a result, the external description of the Fornasini-Marchesini second model is clarified. A technique for designing 2-D recursive digital filters in the frequency domain is then presented by using the Fornasini-Marchesini second model. The resulting filter approximates both magnitude and group delay specifications and its stability is always guaranteed. Finally, three design examples are given to illustrate the utility of the proposed technique.

This study proposes a new training method for hidden Markov model with separate vector quantization (SVQ-HMM) in speech recognition. The proposed method uses the correlation of two different kinds of features: cepstrum and delta-cepstrum. The correlation is used to decrease the number of reestimation for two features thus the total computation time for training models decreases. The proposed method is applied to Japanese language isolated dgit recognition.

Spoken language systems such as speech-to-speech dialog translation systems have been gaining more attention in recent years. These systems require full integration of speech recognition and natural language understanding. This paper presents an efficient parsing algorithm that integrates the search problems of speech processing and language processing. The parsing algorithm we propose here is regarded as an extension of the finite-state-network directed, one-pass search algorithm to one directed by a context-free grammar with retention of the time-synchronous procedure. The extended search algorithm is used to find approximately globally optimal sentence hypotheses; it does not have overhead which exists in, for example, hierarchical systems based on the lattice parsing approach. The computational complexity of this search algorithm is proportional to the length of the input speech. As the search process in the speech recognition can directly take account of the predictive information in the sentence parsing, this framework can be extended to sopken language systems which deal with dynamically varying constraints in dialogue situations.

Parallel multiple context-free grammars (pmcfg's) and multiple context-free grammars (mcfg's) were introduced as extensions of context-free grammars to describe the syntax of natural languages. Pmcfg's and mcfg's deal with tuples of strings, and it has been shown that the universal recognition problem for mcfg's is EXP-POLY time-complete where the universal recognition problem is the problem to decide whether G generates w for a given grammar G and string w. In this paper, the universal recognition problems for the class of pmcfg's and for the subclass of pmcfg's with the information-lossless condition are shown to be EXP-POLY time-complete and PSPACE-complete, respectively. It is also shown that the problems for pmcfg's and for mcfg's with a bounded dimension are both -complete and those for pmcfg's and for mcfg's with a bounded degree are both -complete. As a corollary, the problem for modified head grammars introduced by Vijay-Shanker, et al. to define the syntax of natural languages is shown to be in deterministic polynomial time.

A method for sweeping frequency ranges of over 130GHz within a tuning range of 30nm, without mode hopping, has been realized. The optical frequency is swept with a fine translation-rotation grating drive which uses a new, simplified operation method and a thermally controlled semiconductor laser system.

The selection method of the moment of inertia of the flywheel in a digital measurement system of torque-speed curve plotting for a kind of motor is presented. The selection standards of the moment of inertia and the map displaying the operating ranges of the measurement system are shown. The selection procedure of the moment of inertia is also shown.

Efficient probabilistic decision trees are required in various application areas such as character recognition. This paper presents a polynomial-time approximate algorithm for designing a probabilistic decision tree. The obtained tree is near-optimal for the cost, defined as the weighted sum of the expected test execution time and expected loss. The algorithm is advantageous over other reported heuristics from the viewpoint that the goodness of the solution is theoretically guaranteed. That is, the relative deviation of the obtained tree cost from the exact optimum is not more than a positive constant ε, which can be set arbitrarily small. When the given loss function is Hamming metric, the time efficiency is further improved by using the information theoretical lower bound on the tree cost. The time efficiency of the algorithm and the accuracy of the solutions were evaluated through computational experiments. The results show that the computing time increases very slowly with an increase in problem size and the relative error of the obtained solution is much less than the upper bound ε for most problems.

Recently much attention has been devoted to the problem of translating a set of geometrical objects in a given direction, one at a time, without allowing collisions between the objects. This paper studies the translation problem in three dimensions on a set of c-oriented faces", that is, the faces whose bounding edges have a constant number c of orientations. We solve the problem in O(N log2 NK) time and O(N log N) space, where N is the total number of edges of the faces and K is the number of edge intersections in the projection plane. As an intermediate step, we also solve a problem related to ray-shooting. The algorithm for translating c-oriented faces finds uses in computer graphic systems.