We propose a theory of general frame multiresolution analysis (GFMRA) which generalizes both the theory of multiresolution analysis based on an affine orthonormal basis and the theory of frame multiresolution analysis based on an affine frame to a general frame. We also discuss the problem of perfectly representing a function by using a wavelet frame which is not limited to being of affine type. We call it a "generalized affine wavelet frame." We then characterize the GFMRA and provide the necessary and sufficient conditions for the existence of a generalized affine wavelet frame.

Most research on the estimation of direction of arrival (DOA) has been performed based on the assumption that the signal sources are point sources. In some real surroundings, signal source localization can more adequately be accomplished with distributed source models. When the signal sources are distributed over an area, we cannot directly use well-known DOA estimation methods, because these methods are established based on the point source assumption. In this paper, we propose a 3-dimensional distributed signal source model, in which a source is represented by two parameters, the center angle and degree of dispersion. Then, we address the estimation of the elevation and azimuth angles of distributed sources based on the parametric distributed source modeling in the 3-dimensional space.

This paper introduces a new method to recover 3-D road plane from its 2-D monocular perspective image. The research is aimed at the reconstruction of depth information from the 2-D visual input in road following and navigation. Planar road model is considered and the road-centered coordinate system which forms slope and turn angles with camera-centered coordinate system is used to describe boundary points on road plane. We develop approaches to find matching points of boundaries of road and to obtain angular parameters thereafter. A way of finding depth of matching points from the perspective images and angular parameters together is proposed. Therefore the 3-D road reconstruction can be replicated without introducing any parameters of inverse perspective.

A mesh spiral network (MSnet) and a mesh random (MRnet) are proposed. The MSnet consists of the 2-D torus and bypass links that keep the degree at six. The MRnet consists of the 2-D torus and random bypass links that keep the degree at six. The diameter and the average distance are calculated by using a computer program. The cost of the MSnet is slightly higher than that of the de Bruijn graph, and is about the same as the Star graph. The cost of the MRnet is better than that of the de Bruijn graph. The MSnet is proven to be maximally fault-tolerant. The upper bound of the MRnet size is also discussed.

This paper proposes a hierarchical parallel processing system for the multipass rendering method. The multipass rendering method based on the integration of radiosity and ray-tracing can synthesize photo-realistic images. However, the method is also computationally expensive. To accelerate the multipass rendering method, the system, called (Mπ)2, employs two kinds of parallel processing schemes. As a coarse-grain parallel processing, object-space parallel processing with multiple processing elements based on the object-space subdivision is adapted, and each processing element (PE) is equipped with multiple pipelined units for a fine-grain parallel processing. To balance load among the system, static load balancing at the PE level and dynamic load balancing at the pipelined unit level within the PE are introduced. Especially, we propose a novel static load allocation scheme, skewed-distributed allocation, which can effectively distribute a three-dimensional object space to one- or two-dimensional processor configuration of the (Mπ)2 system. Simulation experiments show that the two-dimensional (Mπ)2 systems with the skewed-distributed allocation outperform the three-dimensional systems with the non-skewed distributed allocation. Since lower dimensional systems can be built at a lower cost than higher dimensional systems, the skewed-distributed allocation will be meritorious. Besides, by the combination of static load balancing by the skewed-distributed allocation and the dynamic load balancing by dynamic ray allocation within each PE, the system performance can be further boosted. We also propose a cached frame buffer system to relieve access collision on a frame buffer.

Adapting the principle of parametron oscillation, a small implantable temperature sensor requiring no internal power supply is described. Since this sensor's oscillation frequency is half that of the excitation frequency, the oscillated signal can be measured from the reception side, free of any signal, interference, simply by positioning the sensor and the excitation antenna so that; 1) they are separated up to 95 cm in the air; 2) a 41 cm gap, the phantom equivalent of the thickness of the human abdomen maintain between them. In the temperature-dependent quartz resonator sensor, oscillation occurs only when frequency and temperature correspond. The excitation power is then adjusted so that the frequency bandwidth narrows. As a result, the margin of error in measuring the temperature is minimized; (0.07).

The purpose of this letter is to investigate the stability of the active two port networks having some restrictions on load and source terminations, and the stability conditions having two inequalities have been obtained. As the terminations making the active two port networks stable can be obtained from these inequalities, these stability conditions are very useful for designing high frequency amplifiers, especially, tuned amplifiers.

We present a minimal lattice realization of MIMO linear discrete-time systems which interpolate the desired Markov and covariance parameters. The minimal lattice realization is derived via a recursive construction algorithm based on the state space description and it parametrizes all the interpolants.

This paper presents a vision-based human interface system that enables a user to move a target object in a 3D CG world by moving his hand. The system can interpret hand motions both in a frame fixed in the world and a frame attached to the user. If the latter is chosen, the user can move the object forward by moving his hand forward even if he has changed his body position. In addition, the user does not have to keep in mind that his hand is in the camera field of view. The active camera system tracks the user to keep him in its field of view. Moreover, the system does not need any camera calibration. The key for the realization of the system with such features is vision algorithms based on the multiple view affine invariance theory. We demon-strate an experimental system as well as the vision algorithms. Human operation experiments show the usefulness of the system.

A new airborne rain radar named CAMPR (CRL Airborne Multiparameter precipitation Radar) has been developed for the major purpose of calibrating PR (Precipitation Radar) onboard TRMM (Tropical Rainfall Measuring Mission; scheduled to be launched in 1997) in orbit by observing the same rain with both CAMPR and TRMM satellite. CAMPR operates as a coherent radar at 13.8 GHz, the same frequency as TRMM-PR, and has polarimetric and Doppler capabilities. It is installed on a relatively small aircraft and can scan the antenna over a wide angle range, from the nadir to the near-horizon. These functions have been verified to work well and it is shown that the radar system is accurately calibrated. Examples of measurement data show CAMPR's high capability to extract various quantities relating to precipitation and cloud physics. Before the TRMM launch, CAMPR is being used to obtain TRMM-PR simulation data to help its algorithm development as well as to obtain data concerning precipitation and cloud physics.

A verification is made on the accuracy of Radar-AMeDAS precipitation, which represents hourly precipitation over the Japanese Islands and the surrounding sea area with a spatial resolution of 5km using data from 5cm conventional radars, 10cm Fujisan Radar, and Automated Meteorological Data Acquisition System (AMeDAS) raingauge network. By comparing with data from a very dense raingauge network of the Tokyo Metropolitan Government, it is found that 1) Radar-AMeDAS precipitation shows good agreement if a positioning error of one pixel of 5km square is allowed 2) Radar-AMeDAS precipitation represents almost the average of raingauge measurements in the 5km square for most of the precipitation caused by a large scale disturbance, and 3) Radar-AMeDAS precipitation is close to the maximum raingauge measurement in the pixel when precipitation is extremely localized such as thunderstorms or showers. Radar-AMeDAS precipitations are compared also with AMeDAS measurements statistically with respect to the appearance rates, that is (total number of pixels where specific intensity is observed) / (total number of all pixels), for different precipitation intensities. The rate of Radar- AMeDAS precipitation shows excellent agreement with that of AMeDAS if radar echoes are observed at the altitude lower than 2km. Since Radar- AMeDAS precipitation on land sometimes represents the maximum of precipitation in a pixel for the purpose of unfailingly detecting extremely localized severe precipitation, it shows a high appearance rate at high precipitation intensity than AMeDAS, which is considered to represent statistically the average of a pixel. As a result, in estimating areal rainfall amounts, Radar- AMeDAS precipitation overestimates AMeDAS measurement by 8% at 5mm/h and by 12% at 40mm/h. Radar- AMeDAS precipitation over the sea, with no local calibration by AMeDAS and with little influence of orography, is 2% weaker in intensity than AMeDAS at 10mm/h, and 12% at 40mm/h.

We present a new method for the identification of time-invariant multichannel autoregressive (AR) processes corrupted by additive white observation noise. The method is based on the Yule-Walker equations and identifies the autoregressive parameters from a finite set of measured data. The input signals to the underlying process are assumed to be unknown. An inverse filtering technique is used to estimate the AR parameters and the observation noise variance, simultaneously. The procedure is iterative. Computer simulation results that demonstrate the performance of the identification method are presented.

A new superresolution technique is proposed for high-resolution estimation of the scattering analysis. For complicated multipath propagation environment, it is not enough to estimate only the delay-times of the signals. Some other information should be required to identify the signal path. The proposed method can estimate the frequency characteristic of each signal in addition to its delay-time. One method called modified (Root) MUSIC algorithm is known as a technique that can treat both of the parameters (frequency characteristic and delay-time). However, the method is based on some approximations in the signal decorrelation, that sometimes make problems. Therefore, further modification should be needed to apply the method to the complicated scattering analysis. In this paper, we propose to apply a time-domain null filtering scheme to reduce some of the dominant signal components. It can be shown by a simple experiment that the new technique can enhance estimation accuracy of the frequency characteristic in the Root-MUSIC algorithm.

A novel reactive congestion control scheme based on Dynamic UPC/NPC (Usage/Network Parameter Control) in ATM networks is proposed. In this scheme, policing parameters at the UPC/NPC are dynamically modified in response to the reception of RM (Resource Management) cells. In a congested state, traffic volume submitted to the network is regulated by Dynamic UPC/NPC, while providing negotiated QoS (Quality of Service) for each ATM connection. When end-stations (or edge-entities between network segments) operate according to ER-based (Explicit Rate based) behavior, a UPC/NPC function will indicate (send) an ER value toward each source end-station using backward RM cells. In this case, the policing parameter at the UPC/NPC should take the same value as the ER value. When end-stations (or edge-entities) operate according to EFCI-based (Explicit Forward Congestion Indication based) behavior, the modified policing parameter at the UPC/NPC point must be harmonized with the modified cell transmission rate at the source end-stations (or at the edge-entities). In order to improve the control performance for the long distance connections, backward RM cells will be generated by the NPC function (UPC function will be optional) at the egress of a congested network in response to the reception of EFCI marked cells (or forward RM cells) as a proxy destination end-station, and they will be sent back toward the UPC/NPC function at the ingress of the network. As a result, the proposed control scheme enables the network to recover from the congested state securely and provide the negotiated service quality, even if cooperation of (rate-based) flow control at each source end-station (and at edge-entities between network segments) is not expected.

In ATM networks Connection Admission Control (CAC) is a key part of traffic control but several challenging problems still remain. One is how to assign sufficient bandwidth fast enough to achieve real-time CAC. Although solutions to the bandwidth assignment problem have been proposed, they require a lot of calculations depending on the number of VCs and on the number of different VC types. Therefore, it is difficult to apply these solutions to real-time CAC decisions, This paper presents a cell-loss ratio evaluation algorithm that takes the peak and the average cell rates as inputs, and providers the upper-bound of the cell-loss ratio. The most remarkable characteristic of this algorithm is that it does not require exhaustive calculation and its calculation load is independent of the number of VCs and the number of different VC types. Using this approximation, we propose a real-time CAC. The experimental results show that call processing of the proposed CAC using a processor, whose pertormance is almost the same as that of a processor in a conventional PBX, terminates within several milliseconds.

The properties of the optical-microwave mixing process are investigated in detail. To describe these processes a new approach, the parametric method is introduced which provides a better description of the mixing phenomenon. The paper presents new experimental results on and new theoretical analysis methods for the optical-microwave mixing process and also for its dynamic behavior. The dynamic properties are very important in many applications when the light is intensity modulated by a high frequency or high bit rate signal. A remarkable decrease is observed in the mixing product with increasing optical modulation frequency. There are two reasons for it: the time constant exhibited by the depletion region between the substrate and the epitaxial layer and the optically induced substrate current which is increasing with the modulation frequency and doesn't contribute to the mixing effect. Understanding the optical-microwave mixing process provides new solutions for many applications. For example the optical-microwave mixing techniques offers several advantages in case of optical reception. In the detection process the modulation signal can be transposed to an intermediate frequency band (instead of the baseband) making possible a lower noise reception in a wider band. Another important and advantageous application is in the reception of subcarrier modulated optical signals.

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 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 disturbance-rejection problem is to find a feedback control law for linear control systems such that the influence of disturbances is completely rejected from the output. In 1970 Wonham and Morse first studied this problem in the framework of the so-called geometric approach. On the other hand, in 1985 Ghosh studied parameter insensitive disturbance-rejection problems with state feedback and with dynamic compensator. In this paper we study the parameter insensitive disturbance-rejection problem with static incomplete-state feedback for linear multivariable systems in the framework of the geometric approach from the mathematical point of view. Necessary conditions and/or sufficient conditions for this problem to be solvable are presented. Finally an illustrative example is presented.

It is important to analyze a tracking or synchronizing process in Spread Spectrum (SS) receiving system. The most common SS tracking system considered here consists of pseudorandom (PN) generator, Lowpass Filter (LPE) and Voltage Controlled Oscillator (VCO). The SS receiver is to track or synchronize its local PN generator to the received PN waveform by VCO. The fundamental equation of the system is known by a second order nonlinear differential equation in terms of phase difference between local PN generator and received PN waveform. The differential equation is nonautonoumous due to PN function of time t with period T. Picking up the gain of VCO as the main parameter in the system we show that the system has bifurcation from the normal oscillation through subharmonic oscillation to finally chaos. In the final case, chaos is confirmed by investigating maximum Liapunov number and both stable and unstable manifolds.