A continuous-wave ultrasonic Doppler system using wide field ultrasound transducers was applied to telemeter blood velocity from the carotid artery of exercising subjects. Velocity spectrogram was obtained by Hanning windowed fast Fourier transformation of the telemetered data. Distortion caused by a high-pass filter and transducers in the telemetry system was discussed in the paper. As the maximum Reynolds number in our experiment was 1478 which is smaller than the critical level of 2000, the blood flow should be laminar. Spatial velocity profiles were then reconstructed from the velocity spectrogram. In this paper, we defined a converging index Q of the velocity spectrum to measure the bluntness of the spatial velocity distribution across the blood vessel. Greater Q, the blunter the velocity profile will be. Simulation results for spatial velocity distributions of theoretical parabolic flow and Gaussian-distribution spectra with varied Q value showed that the cut-off effect by a high-pass filter of cut-off frequency fc=200Hz in our system could be ignored when the axial velocity is larger than 0.30 m/s and Q is greater than 2.0. Our experimental results, in contrast to those obtained from phantom systems by us and by Hein and O'Brien, indicate that the distribution of blood velocity is much blunter than previously thought. The Q index exceeded 10 during systole, whereas it was 0.5 in parabolic flow. The peak of Q index lagged behind that of axial blood velocity by approximately 0.02s. The phase delay of the Q index curve might be due to the time needed for the red blood cells to form the non-homogeneous distribution.

The aliasing probability was analyzed for MISRs when the error probability for each input was different. A closed form expression was derived by applying the complete weight distributions of linear codes over a Galois field and its dual codes. The aliasing probability for MISRs characterized by non-primitive polynomials was also analyzed. The inner product for binary representation of symbols was used instead of multiplication over a Galois field. The results show the perfect expression for analyzing the aliasing probability of MISRs.

In this paper, the discrimination of ultrasonic heart (echocardiographic) images is studied by making use of some texture features, including the angular second moment, contrast, correlation and entropy which are obtained from a gray-level cooccurrence matrix. Features of these types are used as inputs to the input layer of a neural network (NN) to classify two sets of echocardiographic images-normal heart and dilated cardiomyopathy (DCM) (18 and 13 samples, respectively). The performance of the NN classifier is also compared to that of a minimum distance (MD) classifier. Implementation of our algorithm is performed on a PC-486 personal computer. Our results show that the NN produces about 94% (the confidence level setting is 0.9) and the MD produces about 84% correct classification. We notice that the NN correctly classifies all the DCM cases, namely, all the misclassified cases are of false positive. These results indicate that the method of feature-based image analysis using the NN has potential utility for computer-aided diagnosis of the DCM and other heart diseases.

This work deals with thermal-noise modeling for silicon vertical bipolar junction transistors (BJTs) and relevant integrated circuits (ICs) operating at low currents. The two-junction BJT compact model is consistently derived from the thermal-noise generalization of the Shockley semiconductor equations developed in work which treats thermal noise as the noise associated with carrier velocity fluctuations. This model describes BJT with the Itô non-linear stochastic-differential-equation (SDE) system and is suitable for large-signal large-fluctuation analysis. It is shown that thermal noise in silicon p-n-junction diode contributes to "microplasma" noise. The above model opens way for a consistent-modeling-based design/optimization of bipolar device noise performance with the help of theory of Itô's SDEs.

This paper presents testing methods for a logic synthesis system which supports the standard HDL UDL/I, focusing on conformance test to the language specification. Conformance test, to prove that the system completely satisfies the language specification, is very important to provide a unified design environment for users of CAD tools which support the language. The basic idea of our testing methods is using a logic simulator, due to a limited schedule for the test execution. We classified the test into two: unit test and integration test. Unit test is a test of each individual functionality of the system, and integration test is a test to prove that the whole system works correctly and satisfies the language specification. And we prepared and used various kinds of test data. One of them is the UDL/I Test Suite and it was also utilized to observe progress of language coverage by the system during the test execution.

We have developed a design technique for static logic circuits. Using this technique, we designed 1/2 divider-type 1:4 demultiplexer (DEMUX) and 2:1 selector-type 4:1 multiplexer (MUX) circuits, each of which is a key component in high-speed data multiplexing and demultiplexing. These circuits consist of double rail flip-flops (DR F/F). These flip-flops have a smaller mean internal capacitance than single rail flip-flops, making them suitable for high-speed operation. The DR F/F has a symmetric structure, so the double rail toggle flip-flop can put out an exactly balanced CK/CKN signal, which boosts the speed of the data flip-flops. The double rail structure enables 30% faster operation but consumes only 17% more power (per GHz) than a single rail circuit. In addition, our 0.25-µm process technology provides a 70% higher frequency operation than 0.5-µm process technology. At the supply voltage of 2.2 V, the DEMUX circuit and the MUX circuit operate at 4.55 GHz and 2.98 GHz, respectively. In addition, the 0.25-µm DEMUX circuit and the MUX circuit respectively consume 6.0 mW/GHz and 13.7 mW/GHz (＠1.3 V), which are only 12% of the power consumed by 3.3-V 0.5-µm circuits. Because of its high-speed and low-power characteristics, our design technique will greatly contribute to the progress of large-scale high-speed telecommunication systems.

We have developed a method to automatically generate a multi-input-adder circuit for an irregular array of partial products. "FASTOOL," an FIR Filter Automatic Synthesis TOOL for an HDL design environment, is proposed for use with this method and with conventional filter coefficient design programs. Filter design from specifications to the structure of Verilog-HDL has been automated. It is possible for a system designer to quickly perform filter LSI optimization by balancing cost and performance.

CAMs (Content Addressable Memories) are functional memories which have functions such as word-parallel equivalence search, bilateral 1-bit data shifting between consecutive words, and word-parallel writing. Since CAMs can be integrated because of their regular structure, massively parallel CAM functions can be executed. Taking advantage of CAMs, Ishiura and Yajima have proposed a parallel fault simulation algorithm using a CAM. This algorithm, however, requires a large amount of CAM storage to simulate large-scale circuits. In this paper, we propose a new massively parallel fault simulation algorithm requiring less CAM storage, and compare it with Ishiura and Yajima's algorithm. Experimental results of the algorithm on CHARGE --the CAM-based hardware engine developed in our laboratory--are also reported.

We have developed a neutron imaging system based on the penumbral imaging technique. The system consists of a penumbral aperture and a sensitive neutron detector. The aperture was made from a thick (6 cm) tungsten block with a toroidal taper. It can effectively block 14-MeV neutrons and provide a satisfactory sharp, isoplanatic (space-invariant) point spread function (PSF). A two-dimensional scintillator array, which is coupled with a gated two-stage image intensifier system and a CCD camera, was used as a sensitive neutron detector. It can record the neutron image with high sensitivity and high signal-to-noise ratio. The reconstruction was performed with a Wiener filter. The spatial resolution of the reconstructed neutron image was estimated to be 31 µm by computer simulation. Experimental demonstration has been achieved by imaging 14-MeV deuterium-tritium neutrons emitted from a laser-imploded target.

In order to evaluate quantitatively TMJ sound, TMJ sound in normal subject group, CMD patient group A with palpable sounds unknown to them, CMD patient group B with palpable sounds known to them, and CMD patient group C with audible sounds were detected by a contact microphone, and frequency analysis of the power spectra was performed. The power spectra of TMJ sound of normal subject group and patient group A showed patterns with frequency values below 100 Hz, whereas the power spectra of patient groups B and C showed distinctively different patterns with peaks of frequency component exceeding 100 Hz. As regards the cumulative frequency value, the patterns for each group clearly differed from those of other groups; in particular the 80% cumulative frequency value showed the greatest difference. From these results, it is assumed that the 80% cumulative frequency value can be used as an effective indicator for quantitative evaluation of TMJ sound.

In this paper we propose a new method for removing the characteristic of the piezoelectric transducer from the received signal in the pulse-echo method so that the time resolution in the determination of transit time of ultrasound in a thin layer is increased. The total characteristic of the pulse-echo system is described by cascade of distributed-constant systems for the ultrasonic transducer, matching layer, and acoustic medium. The input impedance is estimated by the inverse matrix of the cascade system and the voltage signal at the electrical port. From the inverse Fourier transform of input impedance, the transit time in a thin layer object is accurately determined with high time resolution. The principle of the method is confirmed by simulation experiments.

There have been many developments on neural network research, and ability of a multi-layered network for classification of multi-spectral image data has been studied. We can classify non-Gaussian distributed data using the neural network trained by a back-propagation method (BPM) because it is independent of noise conditions. The BPM is a supervised classifier, so that we can get a high classification accuracy by using the method, so long as we can choose the good training data set. However, the multi-spectral data have many kinds of category information in a pixel because of its pixel resolution of the sensor. The data should be separated in many clusters even if they belong to a same class. Therefore, it is difficult to choose the good training data set which extract the characteristics of the class. Up to now, the researchers have chosen the training data set by random sampling from the input data. To overcome the problem, a hybrid pattern classification system using BPM and Kohonens feature mapping (KFM) has been proposed recently. The system performed choosing the training data set from the result of rough classification using KFM. However, how the remotely sensed data had been influenced by the KFM has not been demonstrated quantitatively. In this paper, we propose a new approach using the competitive weight vectors as the training data set, because we consider that a competitive unit represents a small cluster of the input patterns. The approach makes the training data set choice work easier than the usual one, because the KFM can automatically self-organize a topological relation among the target image patterns on a competitive plane. We demonstrate that the representative of the competitive units by principal component analysis (PCA). We also illustrate that the approach improves the classification accuracy by applying it on the classification of the real remotely sensed data.

This paper proposes a new method that can robustly recover 3D structure and 3D motion of 3D moving objects from a few multi-views. It recovers 3D feature points by obtaining intersections of back-projection lines which are connected from the camera's optical centers thorough projected feature points on the image planes corresponding to the different cameras. We show that our method needs only six views to suppress false 3D feature points in most cases by discussing the relation between the occurrence probability of false 3D feature points and the number of views. This discussion gives us a criterion to design the optimal multi-camera system for recovering 3D structure and 3D motion of 3D moving objects. An experimental multi-camera system is constructed to confirm the validity of our method. This system can take images from six different views at once and record motion image sequence from each view over a period of a few seconds. It is tested successfully on recovering the 3D structure of Vinus's plaster head and on recovering the 3D structure and 3D motion of a moving hand.

This paper describes a statistical integration algorithm for color, motion and stereo disparity, and introduces a real-time stereo system that can tell us where and what objects are moving. Regarding the integration algorithm, motion estimation and depth estimation are simultaneously performed by a clustering process based on motion, stereo disparity, color, and pixel position. As a result of the clustering, an image is decomposed into region fragments. Eath fragment is characterized by distribution parameters of spatiotemporal intensity gradients, stereo difference, color and pixel positions. Motion vectors and stereo disparities for each fragment are obtained from those distribution parameters. The real-time stereo system can view the objects with the distribution parameters over frames. The implementation and experiments show that we can utilize the proposed algorithm in real-time applications such as surveillance and human-computer interaction.

This paper proposes an efficient clustering algorithm for region merging. To speed up the search of the best pair of regions which is merged into one region, dissimilarity values of all possible pairs of regions are stored in a heap. Then the best pair can be found as the element of the root node of the binary tree corresponding to the heap. Since only adjacent pairs of regions are possible to be merged in image segmentation, this constraints of neighboring relations are represented by sorted linked lists. Then we can reduce the computation for updating the dissimilarity values and neighboring relations which are influenced by the merging of the best pair. The proposed algorithm is applied to the segmentations of a monochrome image and range images.

In this paper we describa a system for Off-line Recognition of Arabic characters and Numerals. This is based on expressing the machine printed Arabic alpha-numerical text in terms of strokes obtained by MCR (Minimum Covering Run) expression. The strokes are rendered meaningful by a labeling process. They are used to detect the baseline and to provide necessary features for recognition. The features selected proved to be effective to the extent that with simple right to left analysis we could achieve interesting results. The recognition is achieved by matching to reference prototypes designed for the 28 Arabic characters and 10 numerals. The recognition rate is 97%.

UDL/I test suites and UDL/I Simulation/Synthesis Environment had been developed separately in parallel. Both were designed from syntax and semantics definition of UDL/I Language Reference Manual. Through test of the UDL/I Simulation/Synthesis Environment using the UDL/I test suites, quality of the test suites and the environment had been improved. Finally all the testing result matched with expected one. It was validated that both the test suites and the environment followed UDL/I language specification.

This paper presents a new method for solving the structure-from-motion problem for optical flow. The fact that the structure-from-motion problem can be simplified by using the linearization technique is well known. However, it has been pointed out that the linearization technique reduces the accuracy of the computation. In this paper, we overcome this disadvantage by correcting the linearized solution in a statistically optimal way. Computer simulation experiments show that our method yields an unbiased estimator of the motion parameters which almost attains the theoretical bound on accuracy. Our method also enables us to evaluate the reliability of the reconstructed structure in the form of the covariance matrix. Real-image experiments are conducted to demonstrate the effectiveness of our method.

The wavelet transform provides information both in the spatial domain and in the frequency domain because of its inherent nature of space-frequency analysis. This paper presents a classification result of synthetic aperture radar image obtained by JERS-1 based on the discrete wavelet transform. This paper points out that the wavelet analysis has yielded a fine result in texture classification compared to a conventional method with less computation time.

This paper presents some tighter bounds on universal noiseless coding, in particular, the lowerbound tighter than Davisson et al.'s for finite sequence and the upperbound for some typical universal data compression. We find that Davisson et al.'s bound satisfies some optimization in the case of using the Jeffreys prior and also that the derived upperbound in this paper is within O(1/n) from the Clarke and Barron asymptotics in the case of some restricted typical universal data compression defined in the paper.