Exact analytical solutions for the steady-state transmission and reflection characteristics of a nonlinear Fabry-Perot resonator applicable to bistable optical devices are derived. The resonator consists of a Kerr-like nonlinear film sandwiched by reflection mirrors made of a quarter-wave dielectric stack. An equivalent mirrorless model has been introduced to facilitate the analysis. For both positive and negative nonlinear coefficients, the rigorous solutions have been simply expressed in terms of Jacobian elliptic functions.

We can understand and recover a scene even from a picture or a line drawing. A number of methods have been developed for solving this problem. They have scarcely aimed to deal with scenes of multiple objects although they have ability to recognize three-dimensional shapes of every object. In this paper, challenging to solve this problem, we describe a method for deciding configurations of multiple objects. This method employs the assumption of coplanarity and the constraint of occlusion. The assumption of coplanarity generates the candidates of configurations of multiple objects and the constraint of occlusion prunes impossible configurations. By combining this method with a method of shape recovery for individual objects, we have implemented a system acquirig a three-dimensional information of scene including multiple objects from a monocular image.

We have made an exhaustive computation to establish that 33 comparisons never sort 13 items. The computation was carried out within 10 days by a workstation. Since merge insertion sort [Ford, et al. A tournament problem, Amer. Math. Monthly, vol. 66, (1959)] uses 34 comparisons for sorting 13 items, our result guarantees the optimality of the sorting procedure to sort 13 items as far as the number of comparisons is concerned. The problem has been open for nearly three decades since Mark Wells discovered that 30 comparisons are required to sort 12 items in 1965.

ACk is the class of problems solvable by an alternating Turing machine in space O(log n) and alternation depth O(logk n) [S. A. Cook, A taxonomy of problems with fast parallel algorithms, Inform. Contr. vol. 64]. We consider a game played by two persons: each player alternately moves a marker along an edge of a given digraph, and the first palyer who cannot move loses the game. It is shown that the problem to determine whether the first player can win the game on a digraph with n nodes exactly after logk n moves is complete for ACk nuder NC1 reducibility.

We studied the selective epitaxy of GaAs grown by a technique called pulsed-jet epitaxy. Pulsed-jet epitaxy is a kind of atomic layer epitaxy (ALE) based on low-pressure metalorganic vapor-phase epitaxy (MOVPE). We compared growth behavior and layers grown by ALE and MOVPE. During ALE we supplied trimethylgallium (TMGa) and arsine (AsH3) alternately; however, during MOVPE we supplied TMGa and AsH3 simultaneously. At a growth temperature of 500, we obtained a better growth selectivity using ALE than using MOVPE. The lateral thickness profile of the ALE-grown GaAs layer at the edge of SiO2 mask was uniform. In contrast, the MOVPE growth rate was enhanced near the mask edge. Using ALE, we selectively grew GaAs epilayers even at mask openings with submicron widths. Scanning electron microscopy revealed that the ALE selectively grown structures had an uniform thickness profile, though the facets surrounding the structures depended on the orientation of mask stripes. After MOVPE, however, the (001) surface of the deposited layer was not flat because of the additional lateral diffusion of the growth species from the gas phase and/or the mask surface and some crystal facets. The experimental results show that, using ALE, we can control the shape of selectively grown structures. Selective epitaxy by ALE is a promising technique for fabricating low-dimensional quantum effect devices.

Radar signals fluctuate because of the incoherent scattering of raindrops. Dual-polarization radar estimates rainfall rates from differential reflectivity (ZDR) and horizontal reflectivity (ZH). Here, ZDR and ZH are extracted from fluctuating radar signals by averaging. Therefore, instrumentally measured ZDR and ZH always have errors, so that estimated rainfall rates also have errors. This paper evaluates rainfall rate errors caused by signal fluctuation. Computer simulation based on a physical raindrop model is used to investigate the standard deviation of rainfall rate. The simulation considers acquisition time, and uses both simultaneous and alternate sampling of horizontal and vertical polarizations for square law and logarithmic estimators at various rainfall rates and elevation angles. When measuring rainfall rates that range from 1.0 to 10.0mm/h with the alternate sampling method, using a logarithmic estimator at a relatively large elevation angle, the estimated rainfall rates have significant errors. The simultaneous sampling method is effective in reducing these errors.

In this paper, we analyze high-Tc superconducting (HTS) microstrip antenna (MSA) using modified spectral domain moment method. Although it is assumed that the patch and the ground plane of the MSA are perfect electric conductors (PECs) in the conventional spectral domain method, we modify this method to compute the conduction loss of the HTS-MSA. In our analysis, the effect of the HTS film is introduced by the surface impedance which we can estimate by using the three fluid model and experimental results. This paper presents numerical results about the HTS-MSA, for example, the relations between the thickness of the substrate and the radiation efficiency, the temperature and the resonant frequency, and so forth. And we discuss the effective power range where the performance of the HTS-MSA is superior to that of the Cu-MSA.

In this paper we propose a new algorithm for recognizing 3-D objects from 2-D images. The algorithm takes the multiple view approach in which each 3-D object is modeled by a collection of 2-D projections from various viewing angles where each 2-D projection is called an object model. To select the candidates for the object model that has the best match with the input image, the proposed algorithm computes the surface matching score between the input image and each object model by using Hopfield nets. In addition, the algorithm gives the final matching error between the input image and each candidate model by the error of the pose-transform matrix proposed by Hong et al. and selects an object model with the smallest matching error as the best matched model. The proposed algorithm can be viewed as a combination of the algorithm of Lin et al. and the algorithm of Hong et al. However, the proposed algorithm is not a simple combination of these algorithms. While the algorithm of Lin et al. computes the surface matching score and the vertex matching score berween the input image and each object model to select the candidates for the best matched model, the proposed algorithm computes only the surface matching score. In addition, to enhance the accuracy of the surface matching score, the proposed algorithm uses two Hopfield nets. The first Hopfield net, which is the same as that used in the algorithm of Lin et al., performs a coarse matching between surfaces of an input image and surfaces of an object model. The second Hopfield net, which is the one newly proposed in this paper, establishes the surface correspondences using the compatibility measures between adjacent surface-pairs of the input image and the object model. the results of the experiments showed that the surface matching score obtained by the Hopfield net proposed in this paper is much more useful for the selectoin of the candidates for the best matched model than both the sruface matching score obtained by the first Hopfield net of Lin et al. and the vertex matching score obtained by the second Hopfield net of Lin et al. and, as the result, the object recognition algorithm of this paper can perform much more reliable object recognition than that obtained by simply combining the algorithm of Lin et al. and the algorithm of Hong et al.

This paper proposes RSA-type cryptosystems over elliptic curves En(O, b) and En(a, O),where En(a, b): y2 x3+ax+b (mod n),and n is a product of from-free primes p and q. Although RSA cryptosystem is not secure against a low exponent attack, RSA-type cryptosystems over elliptic curves seems secure against a low multiplier attack. There are the KMOV cryptosystem and the Demytko cryptosystem that were previously proposed as RSA-type cryptosystems over elliptic curves. The KMOV cryptosystem uses form-restricted primes as p q 2(mod 3)or p q 3(mod 4), and encrypts/decrypts a 2log n-bit message over varied elliptic curves by operating values of x and y coordinates. The Demytko cryptosystem, which is an extension of the KMOV cryptosystem, uses form-free primes, and encrypts/decrypts a log n-bit message over fixed elliptic curves by operating only a value of x coordinates. Our cryptosystems, which are other extensions fo the KMOV cryptosystem, encrypt/decrypt a 2log n-bit message over varied elliptic curves by operating values of x and y coordinates. The Demytko cryptosystem and our cryptosystems have higher security than the KMOV cryptosystem because from-free primes hide two-bit information about prime factors. The encryption/decryption speed in one of our cryptosystems is about 1.25 times faster than that in the Demytko cryptosystem.

A specific signal in most of actual environmental systems fluctuates complicatedly in a non-Gaussian distribution form, owing to various kinds of factors. The nonlinearity of the system makes it more difficult to evaluate the objective system from the viewpoint of internal physical mechanism. Furthermore, it is very often that the reliable observation value can be obtained only within a definite domain of fluctuating amplitude, because many of measuring equipment have their proper dynamic range and the original random wave form is unreliable at the end of amplitude fluctuation. It becomes very important to establish a new signal processing or an evaluation method applicable to such an actually complicated system even from a functional viewpoint. This paper describes a new trial for the signal processing along the same line of the extended regression analysis based on the Bayes' theorem. This method enables us to estimate the response probability property of a complicated system in an actual situation, when observation values of the output response are saturated due to the dynamic range of measuring equipment. This method utilizes the series expansion form of the Bayes' theorem, which is applicable to the non-Gaussian property of the fluctuations and various kinds of correlation information between the input and output fluctuations. The proposed method is newly derived especially by paying our attention to the statistical information of the input-output data without the saturation operation instead of that on the resultantly saturated observation, differing from the well-known regression analysis and its improvement. Then, the output probability distribution for another kind of input is predicted by using the estimated regression relationship. Finally, the effectiveness of the proposed method is experimentally confirmed too by applying it to the actual data observed for indoor and outdoor sound environments.

Learning correctly from queries" is a formal learning model proposed by Angluin. In this model, for a class Γ of language representations, a learner asks queries to a teacher of an unknown language Lq which can be represented by some GqΓ, and eventually outputs a language representation GΓ which represents Lq and halts. An algorithm (leaner) A is said to learn a class of languages represented by Γ in the weak definition if the time complexity of A is some polynomial of n and m, where n is the minimum size of the lagunage representations in Γ which represent Lq, and m is the maximum length of the counterexamples returned in an execution. On the other band, A is said to learn represented by Γ in the strong definition if at any point τ of the execution, the time consumed up to τ is some polynomial of n and m, where n is the same as above, and m is the maximum length of the counterexamples returned up to τ. In this paper, adequacy of the model is examined, and it is shown that both in the weak and strong definitions, there exist learners which extract a long counterexample, and identify Lq by using equivalence queries exhaustively. For example, there exists a learner which learns the class CFL of context-free languages represented by the class CFG of context-free grammars in the weak definition using only equivalence queries. Next, two restrictions concerning with learnability criteria are introduced. Proper termination condition is that when a teacher replies with yes" to an equivalence query, then the learner must halt immediately. The other condition, called LBC-condition, is that in the weak/strong definition, the time complexity must be some polynomial of n and log m. In this paper, it is shown that under these conditions, there still exist learners which execute exhaustive search. For instance, there exists a learner which learns CFL represented by CFG in the weak definition using membership queries and equivalence queries under the proper termination condition, and there also exists a learner that learns CFL represented by CFG in the strong definition using subset queries and superset queries under LBC-condition. These results suggest that the weak definition is not an adequate learning model even if the proper termination condition is assumed. Also, the model becomes inadequate in the strong definition if some combination of queries, such as subset queries and superset queries, is used instead of equivalence queries. Many classes of languages become learnable by our extracting long counterexample" technique. However, it is still open whether or not CFL represented by CFG is learnable in the strong definition from membership queries and equivalence queries, although the answer is known to be negative if at least one of (1) quadratic residues modulo a composite, (2) inverting RSA encryption, or (3) factoring Blum integers, is intractable.

The performance of multi-pulse pulse position modulation (MPPM) consisting of m slots and 2 pulses, denoted as (m, 2) MPPM, with imperfect slot synchronization is analyzed. The word error probability of (m, 2) MPPM in the presence of timing offset is analyzed, and the optimum symbol sets of (m, 2) MPPM minimizing the symbol error probability are assigned. When an unassigned symbol is detected, the receiver decodes the unassigned symbol as one of the assigned symbols having the highest probability of transition from the assigned symbol to the unassigned symbol. The bit error probability of (m, 2) MPPM in the presence of the timing offset is analyzed, and the bit error probability of (m, 2) MPPM is compared with that of PPM for the same transmission bandwidth and the same transmission rate. Moreover, the bit error probability of (m, 2) MPPM synchronized by a phase-locked loop (PLL) is also analyzed. It is shown that a word with two continuous pulses has better performance than a word with two separate pulses. It is also shown that when the timing offset occurs, and when the slot clock is synchronized by a PLL, (m, 2) MPPM performs better than PPM because (m, 2) MPPM has the optimum assigned symbols, and can decode detected words more correctly than PPM.

A feedback pattern recognition method using an inverse recall neural network model is proposed. The feedback method can adjust processing parameter values adaptively to individual patterns so as to produce reliable recognition results. In order to apply an adaptive control technique to such pattern recognition processings, the evaluation value for recognition uncertainty is determined to be a function with regard to an input pattern and processing parameters. In its feedback phase, the input pattern is fixed and processing parameters are adjusted to decrease the recognition uncertainty. The proposed neural network model implements two functions in this feedback recognition method. One is a discrimination as a kind of multi-layer feedforward model. The other is to generate an input modification so as to decrease the recognition uncertainty. The modification values indicate parts which are important for more certain recognition but are missed in the original input to the nerwork. The proposed feedback method can adjust prcessing parameter values in order to detect the important parts shown by the inverse recall network model. As explained in this paper, feature extraction parameter values are adaptively adjusted by this feedback method. After the inverse recall model and the feedback function are implemented, features are extracted again by using the modified feature extraction parameter values. The feature is classified by the feedforward function of the network model. The feedforward and feedback processings are repeated until a certain recognition result is obtained. This method was examined for hadwritten alpha-numerics with rotation distortion. The feedback method was found to decrease the rejection ratio at the same substitution error ratio with high efficiency.

This paper reviews two topics of nonlinear system analysis done in Japan. The first half of this paper concerns with nonlinear system analysis through the nondeterministic operator theory. The nondeterministic operator is a set-valued or fuzzy set valued operator by K. Horiuchi. From 1975 Horiuchi has developed fixed point theorems for nondeterministic operators. Using such fixed point theorems, he developed a unique theory for nonlinear system analysis. Horiuchi's theory provides a fundamental view point for analysis of fluctuations in nonlinear systems. In this paper, it is pointed out that Horiuchi's theory can be viewed as an extension of the interval analysis. Next, Urabe's theory for nonlinear boundary value problems is discussed. From 1965 Urabe has developed a method of computer assisted existence proof for solutions of nonlinear boundary value problems. Urabe has presented a convergence theorem for a certain simplified Newton method. Urabe's theorem is essentially based on Banach's contraction mapping theorem. In this paper, reformulation of Urabe's theory using the interval analysis is presented. It is shown that sharp error estimation can be obtained by this reformulation. Both works discussed in this paper have been done independently with the interval analysis. This paper points out that they have deep relationship with the interval analysis. Moreover, it is also pointed out that these two works suggest future directions of the interval analysis.

Real-time collision detection is one of the most important intelligent processings in robotics. In collision detection, a large storage capasity is usually required to store the 3-dimensional information on the obstacles located in a workspace. Moreover, high-computational power is essential in not only coordinate transformation but also matching operation. In the proposed collision detection VLSI processor, the matching operation is drastically accelerated by using a content-addressable memory (CAM). A new obstacle representation based on a union of rectangular solids is also used to reduce the obstacle memory capacity, so that the collision detection can be performed by only magnitude comparison in parallel. Parallel architecture using several identical processor elements (PEs) is employed to perform the coordinate transformation at high speed, and each PE performs coordinate transformation at high speed based on the COordinate Rotation DIgital Computation (CORDIC) algorithms. When the 16 PEs and 144-kb CAM are used, the performance is evaluated to be 90 ms.

A 250-MIPS, 125-MFLOPS peak performance processing element (PE), which is being developed for an on-chip multiprocessor, has been modeled and evaluated. The PE includes the following new architecture components: an FPU shared by several IUs in order to increase the efficiency of the FPU pipelines, an on-chip data cache with a prefetch mechanism to reduce clock cycles waiting for memory, and an interface to high speed DRAM, such as Rambus DRAM and Synchronous DRAM. As a result, a PE model with an FPU shared by four or eight IUs causes only 10% performance reduction compared to a model with an un-shared FPU model while saving the cost of three FPUs. Furthermore, a PE model with prefetch operates 1.2 to 1.8 times faster than a model without prefetch at 250-MHz clock rate when the Rambus DRAM is connected. It becomes clear that this PE architecture can bring a high effective performance at over 250-MHz, and is cost-effective for the on-chip multiprocessor.

In robot vision system, enormously large computation power is required to perform three-dimensional (3-D) instrumentation and object recognition. However, many kinds of complex and irregular operations are required to make accurate 3-D instrumentation and object recognition in the conventional method for software implementation. In this paper, a VLSI-oriented Model-Based Robot Vision (MBRV) processor is proposed for high-speed and accurate 3-D instrumentation and object recognition. An input image is compared with two-dimensional (2-D) silhouette images which are generated from the 3-D object models by means of perspective projection. Because the MBRV algorithm always gives the candidates for the accurate 3-D instrumentation and object recognition result with simple and regular procedures, it is suitable for the implementation of the VLSI processor. Highly parallel architecture is employed in the VLSI processor to reduce the latency between the image acquisition and the output generation of the 3-D instrumentation and object recognition results. As a result, 3-D instrumentation and object recognition can be performed 10000 times faster than a 28.5 MIPS workstation.

Finite state translation systems (fsts') are a widely studied computational model in the area of tree automata theory. In this paper, the string generating capacities of fsts' and their subclasses are studied. First, it is shown that the class of string languages generated by deterministic fsts' equals to that of parallel multiple context-free grammars, which are an extension of context-free grammars. As a corollary, it can be concluded that the recognition problem for a deterministic fsts is solvable in O(ne1)-time, where n is the length of an input word and e is a constant called the degree of the deterministic fsts'. In contrast to the latter fact, it is also shown that nondeterministic monadic fsts' with state-bound 2 can generate an NP-complete language.

We propose a beam tracing frame which shifts together with either the guiding structure or the beam propagation in optical circuits. This frame is adaptive to the beam propagation analysis based on the finite-element method and can reduce the computational window size.

Let S(n) be a space constructible function such that S(n) log n. In this paper, we show that AuxSpTu (S(n),T(n)) NSPACE (S(n)log T(n)), where AuxSpTu (S(n),T(n)) is the class of languages accepted by nondeterministic auxiliary pushdown automata operating simultaneously in O(S(n)) space and O(T(n)) turns of the auxiliary tape head.