Genetic algorithms were introduced by Holland in 1975 as a method of solving difficult optimization problems by means of simulated evolution. A major drawback of genetic algorithms is their slowness when emulated by software on conventional computers. Described is an adaptation of the original genetic algorithm that is advantageous to hardware implementation along with the architecture of a hardware framework that performs the functions of population storage, selection, crossover, mutation, fitness evaluation, and survival determination. Programming of the framework is illustrated with the set coverage problem that exhibits a 6,000 speed-up over software emulation on a 100 MHz workstation.

A new method is proposed for estimating a single complex sinusoid and its parameters (frequency and amplitude) from measurements corrupted by white noise. This method is called the ECKF-SVD method, which is derived by applying an extended complex Kalman filter (ECKF) to a nonlinear stochastic system whose state variables consist of the AR coefficient (a function of frequency) and a sample of the original signal. Proof of the stability is given in the case of a single sinusoid. Simulations demonstrate that the proposed ECKF-SVD method is effective for estimating a single complex sinusoid and its frequency under a low signal-to-noise ratio (SNR). In addition, the amplitude estimation by means of the ECKF-SVD method is also discussed.

The defects in the cold rolled strips have textural characteristics, which are nonuniform due to its irregularities and deformities in geometrical appearance. In order to handle the textural characteristics of images with defects, this paper proposes a surface inspection method based on textural feature extraction using the wavelet transform. The wavelet transform is employed to extract local features from textural images with defects both in the frequency and in the spatial domain. To extract features effectively, an adaptive wavelet packet scheme is developed, in which the optimum number of features are produced automatically through subband coding gain. The energies for all subbands of the optimal quadtree of the adaptive wavelet packet algorithm and four entropy features in the level one LL subband, which correspond to the local features in the spatial domain, are extracted. A neural network is used to classify the defects of these features. Experiments with real image data show good training and generalization performances of the proposed method.

This paper describes a novel image reconstruction algorithm and experimental results of a 3-dimensional acoustical holographic imaging system which has a limited number of transducers distributed sparsely. The proposed algorithm is based on the conjugate gradient projection onto convex sets (CGPOCS), which allows the addition of convex sets constrained by a priori information to reduce ambiguity and extract resolution iteratively. By several experiments, it is proven that the concept of the new 3-D acoustic image reconstruction algorithm has following improvements:1. the artifacts caused by the spurious lobes can be reduced under the condition that the inter-spacing of elements is larger than the wave length,2. the instability caused by the lack of information about the actual point spread function (PSF) can be reduced,3. the actual PSF can be estimated concurrently with during the image reconstruction process.

This paper proposes a data-localization scheduling scheme inside a processor-cluster for multigrain parallel processing, which hierarchically exploits parallelism among coarsegrain tasks like loops, medium-grain tasks like loop iterations and near-fine-grain tasks like statements. The proposed scheme assigns near-fine-grain or medium-grain tasks inside coarse-grain tasks onto processors inside a processor-cluster so that maximum parallelism can be exploited and inter-processor data transfer can be minimum after data-localization for coarse-grain tasks across processor-clusters. Performance evaluation on a multiprocessor system OSCAR shows that multigrain parallel processing with the proposed data-localization scheduling can reduce execution time for application programs by 10% compared with multigrain parallel processing without data-localization.

Superposed ATM cell streams have burstiness and strong autocorrelation properties. This paper investigates traffic measurement-based modeling method for superposed ATM cell streams. We develop a new measurement method based on monitoring both the waiting time distribution in a monitoring queue and the autocorrelation of cell interarrival times. Through the monitoring queue, we directly observe the queueing effect of superposed cell flows on ATM multiplexers. The measured traffic is modeled as the two-state MMPP. With the measured traffic, we estimate the cell loss probability in ATM multiplexers from the MMPP/D/1/K queue. Our method successfully works with homogeneous and heterogeneous superposition of traffic sources including voice, data, and video. These results can be applied to the evaluation of ATM multiplexers, traffic engineering, and network performance monitoring.

Periodic reservation allows periodic and random packets to share the same satellite random access channel efficiently. The periodic reservation protocol is particularly suitable for mobile satellite position reporting services, where some of the information messages, such as dispatch function, are classified as "periodic" and others, such as signaling, are classified as "random." When a new mobile terminal logs on to the system, Network Management Center (NMC) reserves subsequent time slots for transmitting periodic packets without contention. A mobile terminal recognizes each time slot as "reserved" or "unreserved (available)" according to the broadcast message received from NMC. Other random packets use the slotted ALOHA protocol to contend with other mobile terminals for an unreserved time slot. The performance results suggest that the use of the periodic reservation protocol can be regarded as a viable solution for mobile satellite position reporting services such as automatic dependent surveillance (ADS).

The fabrication of InAlAs wire structures and InGaAs quantum wire structures on non-planer InP substrates with truncated ridges by molecular beam epitaxy is demonstrated. Indium-rich InAlAs epitaxial layers grown on top of ridges exhibit self-formation of electron-confining InAlAs wire structures. The InAlAs layers on top of the ridges lattice-matched to the substrate are obtained by the control of In flux during the growth. The InGaAs quantum wire structures have been fabricated on thus composition-controlled InAlAs barrier layers. The optical properties of the InGaAs quantum wires with composition-controlled InAlAs barrier layer are found to be better than that of the wires without compositional control.

The multichannel distortions of direct modulated laser diode were studied from the view point of rate equations. A novel technique for compensating the composite second order distortion (CSO) was proposed. Meanwhile, the related calibration procedures were indicated. After the compensation, 10 dB improvement in CSO was obtained

We study individual carrier traps in a GaAs/AlxGa1-xAs heterostructure by observing random telegraph signals. A narrow channel, which is formed in a split gate device, is shifted by independently controlling the voltage applied to each part of the split gate. RTSs can be observed only when the traps are close to the channel and the energy levels of the traps are within a few kBT of the Fermi level. This type of measurement reveals the locations and the energy distributions of the traps. We also discuss the situation in which two trap levels are at the Fermi level simultaneously. In this condition the two RTSs do not occur at the same time, but they do interact with each other. This implies that there is an electrostatic interaction between the two trappings.

Finite-difference time-domain (FDTD) analysis is performed to evaluate the distributions of specific absorption rate (SAR) in a human head during use of a handheld portable telephone. A heterogeneous head model has been assumed which is comprised of 273 108 cubic cells 2.5 mm on a side, with the electrical properties of anatomical equivalents. A handset model has been assumed to be a metal box with either a quarter-wavelength monopole or a half-wavelength dipole operating at 900 MHz or 1.5 GHz. The maximum local SARs in the head are evaluated under various exposure conditions. The dependence of the maximum local SARs on the difference in the structures or parameters of the model, i.e. the distance between the antenna and the head, the heterogeneity of the head, the antenna type, the volume of the smoothing region of the local SAR value, skin electrical constants, and the presence or absence of auricles, are examined. It is shown that the heterogeneity of the head barely affect the maximum local SAR when the telephone is located sufficiently close to the head. It is also shown that the electrical constants of skin which has lower conductivity provide the lower maximum local SAR in the head while the maximum local SAR within the brain is not significantly affected. The auricle which lies in closest proximity to the antenna is shown to have significant effect on the maximum local SAR. It is suggested that the presence of the auricle enhances the maximum local SAR by a factor that is 1.7-2.4 larger than the model without auricles.

Conventional learning algorithms are considered to be a sort of estimation of the true recognition function from sample patterns. Such an estimation requires a good assumption on a prior distribution underlying behind learning data. On the other hand the human being sounds to be able to acquire a better result from an extremely small number of samples. This forces us to think that the human being might use a suitable prior (called presupposition here), which is an essential key to make recognition machines highly flexible. In the present paper we propose a framework for guessing the learner's presupposition used in his learning process based on his learning result. First it is pointed out that such a guess requires to assume what kind of estimation method the learner uses and that the problem of guessing the presupposition becomes in general ill-defined. With these in mind, the framework is given under the assumption that the learner utilizes the Bayesian estimation method, and a method how to determine the presupposition is demonstrated under two examples of constraints to both of a family of presuppositions and a set of recognition functions. Finally a simple example of learning with a presupposition is demonstrated to show that the guessed presupposition guarantees a better fitting to the samples and prevents a learning machine from falling into over learning.

In order to improve the sensitivity of micromachined sensors applied with electrostatic fields and increase their actuated force of electrostatic micromachined actuators, "electrets," which are dielectrics carrying non equilibrium permanent space charges of polarization distribution, are very important. In this paper, positively corona charged silicon dioxide electrets, which are deposited by Plasma Chemical Vapor Deposition (PCVD) and thermally oxidized, are investigated. Physical studies will be described, in which the charge stability is correlated to Thermally Stimulated Current (TSC) measurements and to Electron Spin Resonance (ESR) analysis. Some intrinsic differences have been observed between materials. The electrets with superior long-term charge stability contain 10,000 times as much E' center (Si3 as the ones with inferior long-term charge stability. Finally, some investigations on the long-term charge storage mechanism of the positively charged silicon dioxide electret will be described.

The 4th harmonics of a Nd:YAG laser beam (266 nm) is applied to fabricate highly oriented Y1Ba2Cu3O7-δ -SrTiO3-Y1Ba2Cu3O7-δ multilayer structures. It has been shown that the emission temperature of a film surface will change during deposition, depending on deposition conditions, even though the heater temperature is constant. The change of substrate temperature is strongly correlated to film characteristics such as critical temperature, c-axis length, and resistivity. The insitu monitoring of the substrate temperature is useful for obtaining high-quality Y1Ba2Cu3O7-δ films reproducibly. It is also shown that a SrTiO3 layer prevents oxygen restoration in a Y1Ba2Cu3O7-δ underlayer. The relationship between oxygen deficiency and the annealing conditions is studied.

This paper proposes robust algorithms for linebased pose enumeration from a single view, and it reports on their evaluations by simulations. The proposed algorithms incorporate two major refinements into the algorithms originally proposed by Shakunaga [1]. The first refinement, introduction of zone-crossing detection to the 1-d search remarkably decreases the rate of overlooking a correct pose. The second refinement, adaptive selection of a PAT pair considerably reduces the average estimation error. Simulation results show that pose estimation precision depends primarily on the precision of line detection. Although the refinements are widely effective, they are more effective for more precise line detection. For 99% of rigid body samples, the algorithm can estimate rotation with an error of less than 2 degrees, and for 99.9% of the samples, the error is less than 10 degrees. Simulation experiments for articulated objects show similar results by using the second algorithm. The effectiveness of the algorithms is verified in an alignment approach by simulations.

The objective of this paper is to find a parametric representation for the vocal-tract log-area function that is directly and simply related to basic acoustic characteristics of the human vocal-tract. The importance of this representation is associated with the solution of the articulatory-to-acoustic inverse problem, where a simple mapping from the articulatory space onto the acoustic space can be very useful. The method is as follows: Firstly, given a corpus of log-area functions, a parametric model is derived following a factor analysis technique. After that, the articulatory space, defined by the parametric model, is filled with approximately uniformly distributed points, and the corresponding first three formant frequencies are calculated. These formants define an acoustic space onto which the articulatory space maps. In the next step, an independent component analysis technique is used to determine acoustic and articulatory coordinate systems whose components are as independent as possible. Finally, using singular value decomposition, acoustic and articulatory coordinate systems are rotated so that each of the first three components of the articulatory space has major influence on one, and only one, component of the acoustic space. An example showing how the proposed model can be applied to the solution of the articulatory-to-acoustic inverse problem is given at the end of the paper.

To develop human interface for virtual environment, we have constructed a tensed strings based interface device called SPIDAR, which allow us to manipulate virtual object directly just like in real space. SPIDAR can both measure the movement of user's finger tip and offer force display. Since proper force feedback comes out of the proper position measurement, in this paper, we will analyze the possible reasons that may cause position measurement error, and propose an algorithm which can revise the error and improve position measurement precision.

A structural active-object system (SAOS) is a transition-based object-oriented system suitable for rapid development of hardware logic simulators. A SAOS consists of a collection of interacting structural active objects (SAOs), whose behaviors are determined by the transition statements provided in their class definitions. Furthermore, SAOs can be structurally and hierarchically composed from their component SAOs like hardware components. These features allow SAOs to model components for circuit simulation more naturally than passive objects used in ordinary object-oriented programming. Also, we can easily create new kinds of components by using the inheritance mechanism. Executions of transition statements may be event-and/or time-driven, and hence digital, analog, and mixed-mode simulation is possible. Prototype simulation programs with graphical user interfaces have been developed as SAOS programs for digital, analog, and mixed-mode circuit simulation.

A new postprocessing method using interpolated n-gram model for Japanese documents is proposed. The method has the advantages over conventional approaches in enabling high-speed, knowledge-free processing. In parameter estimation of an n-gram model for a large size of vocabulary, it is difficult to obtain sufficient training samples. To overcome poverty of samples, two smoothing methods for Japanese character trigram model are evaluated, and the superiority of deleted interpolation method is shown by using perplexity. A document recognition system based on the trigram model is constructed, which finds maximum likelihood solutions through Viterbi algorithm. Experimental results for three kinds of documents show that the performance is high when using deleted interpolation method for smoothing. 90% of OCR errors are corrected for the documents similar to training text data, and 75% of errors are corrected for the documents not so similar to training text data.

A new neural network for locating a source by integrating data from a number of sensors is considered. The network gives a solution for inverse problems using a back-propagation algorithm with the architecture to get the solution in the inter-layer weights in a coded form Three different physical quantities are applied to the network, since the scheme has three independent ports; an input port, a tutorial port and an answer port. Our architecture is useful to estimate z" in the problem whose structure is y=f(x,z) where y is the observed data, x is the sensor position and z is the source location. The network integrates the information obtained from a number of sensors and estimates the location of the source. We apply the network to two problems of location estimation: the localization of the active nerves from their evoked potential waveforms and the localization of objects from their echoes using an active sonar system.