We propose a method for the recovery of projective structure and motion by the factorization of the rank 1 matrix containing the images of all points in all views. In our method, the unknowns are the 3D motion and relative depths of the set of points, not their 3D positions. The coordinates of the points along the camera plane are given by their image positions in the first frame. The knowledge of the coordinates along the camera plane enables us to solve the SFM problem by iteratively factorizing the rank 1 matrix. This simplifies the decomposition compared with the SVD (Singular Value Decomposition). Experiments with both simulated and real data show that the method is efficient for the recovery of projective structure and motion.

Fast and simple algorithm of a parity checker for a large residue numbers is presented. A new set of RNS moduli with 2r-(2l1) form for fast modular multiplication is proposed. The proposed RNS moduli has a large dynamic range for a large RNS number. The parity of a residue number can be checked by the Chinese remainder theorem (CRT). A CRT-based parity checker is simply organized by the Montgomery reduction method (MRM), implemented by using multipliers and the carry-save adder array. We present a fast parity checker with minimal hardware processed in three clock cycles for 32-bit RNS modulus set.

We observed the optically forbidden energy transfer between cubic CuCl quantum dots coupled via an optical near-field interaction using time-resolved near-field photoluminescence (PL) spectroscopy. The energy transfer time and exciton lifetime were estimated from the rise and decay times of the PL pump-probe signal, respectively. We found that the exciton lifetime increased as the energy transfer time fell. This result strongly supports the notion that near-field interaction between QD makes the anti-parallel dipole coupling. Namely, a quantum-dots pair coupled by an optical near field has a long exciton lifetime which indicates the anti-parallel coupling of QDs forming a weakly radiative quadrupole state.

This paper presents a wide frequency range delay-locked loop implemented with a 0.35 µm CMOS technology, which can overcome the limited frequency range and false lock problem of conventional delay-locked loop (DLL). The proposed simple DLL architecture comprising frequency and phase detector has better process-portability. The implemented DLL covers frequency range from 10 MHz to 200 MHz, which is limited only by the characteristics of delay cell. The DLL consumes 19.8 mW and shows 13 ps rms jitter at 3.3 V, 150 MHz condition.

Estimation of unknown signal parameters with sensor array measurements has been investigated quite extensively. Also, there has been in recent years an explosive increase in the number of mobile users in wireless cellular systems, thus contributing to growing levels of multi-user interference. To overcome this problem, application of adaptive antenna array techniques to further increase the channel capacity has been discussed. In this paper, a new model of locally scattered signals in the vicinity of mobiles is proposed by defining the mean steering vector and manipulate it mathematically for several distributions. Under this model an estimation method of the direction of arrival is investigated based on a weighted subspace fitting technique. Statistical analysis and simulations are also considered.

The issue of importance of multiuser detection for CDMA-based mobile ad hoc networks is addressed in this paper. For conventional scheme, each terminal in the network uses matched filter to receive packets, so the performance (e.g., throughput) of the network suffers from multi-access interference (MAI). Different from above scheme, in this paper, each terminal of the ad hoc network is equipped with an adaptive blind linear multiuser detector, so the ability of MAI-resistance is gained. Employing slotted-ALOHA protocol in MAC layer and using fully-connected network model, the throughput of ad hoc network is studied. Theoretic analysis and simulation results show that multiuser detection can remarkably improve throughput performance of ad hoc networks.

An active network has the advantage of being able to accept new protocols quickly and easily. The cluster-based active router can provide sufficient computing power for customized computations. In the router architecture, load balancing is achieved by the efficient distribution of packets. We present a packet distribution scheme according to estimated processing time.

In this paper, we present the method for identifying an Adaptive Neuro-Fuzzy Networks (ANFN) with Takagi-Sugeno-Kang (TSK) fuzzy type based on fuzzy granulation. We also develop a systematic approach to generating fuzzy if-then rules from a given input-output data. The proposed ANFN is designed by the use of fuzzy granulation realized via context-based fuzzy clustering. This clustering technique builds information granules in the form of fuzzy sets and develops clusters by preserving the homogeneity of the clustered patterns associated with the input and output space. The experimental results reveal that the proposed model yields a better performance in comparison with Linguistic Models (LM) and Radial Basis Function Networks (RBFN) based on context-based fuzzy clustering introduced in the previous literature for Box-Jenkins gas furnace data and automobile MPG prediction.

In this paper, we propose an agent architecture for a combination of speculative computation and abduction. Speculative computation is a tentative computation when complete information for performing computation is not obtained. We use a default value to complement such incomplete information. Unlike usual default reasoning, the real value for the information can be obtained during the computation and the computation can be revised on the fly. In the previous work, we applied this technique to handling distributed problem solving under incomplete communication environments in the context of multi-agent systems and proposed correct procedures in abductive logic programming in terms of perfect model semantics. In the previous work, however, we regarded assumptions as defaults and used these assumptions for speculative computation. Thus, we could not perform hypothetical reasoning, that is, the original usage of abduction. In this paper, we extend our framework so that speculative computation and abduction can be both performed. As a result, our procedure becomes an extension of the abductive procedure developed by Kakas and Mancarella augmented by dynamic belief revision mechanism about outside world.

This letter proposes two very-low-complexity maximum-likelihood (ML) detection algorithms based on QR decomposition for the quasi-orthogonal space-time code (QSTBC) with four transmit antennas [3]-[5], called VLCMLDec1 and VLCMLDec2 decoders. The first decoder, VLCMLDec1, can be used to detect transmitted symbols being extracted from finite-size constellations such as phase-shift keying (PSK) or quadrature amplitude modulation (QAM). The second decoder, VLCMLDec2, is an enhanced version of the VLCMLDec1, developed mainly for QAM constellations. Simulation results show that both of the proposed decoders enable the QSTBC to achieve ML performance with significant reduction in computational load.

A novel phase error correction scheme is proposed for the high rate OFDM-based wireless local area networks (WLANs). The proposed scheme makes the system capable of efficiently compensating the whole phase error due to the residual sampling clock offset and frequency offset estimation error after timing and frequency offset compensation, as well as the phase noise.

A new expression for cell/packet loss probability in an ATM and packet switched queue system with a finite buffer is presented. Cell and packet loss analysis is based on the new concept of a "buffer overflow cluster" and the overflow probability for a queue with an infinite buffer. This approach holds for a wide variety of long-range dependent traffic sources typical of wide-area networks, as well as Internet and other communication traffics. The method is verified by simulations of two long-range dependent traffic scenarios: fractional Gaussian noise and multifractal wavelet model traffic with a beta marginal distribution.

Deflection routing is one of the promising approaches to resolve contention in the optical burst switching networks. In the conventional deflection routing scheme, optical bursts may be unable to traverse the route evaluated to select an outgoing link because of the contention at succeeding downstream transit nodes. As a result, the optical bursts may traverse a different route resulting in a long distance or decreased performance. This paper proposes a deflection routing scheme that considers the possibility of the contention at downstream nodes. This scheme utilizes the "expected route distance" instead of the static route distance toward a destination node. The expected route distance considers the possibility of contention at each downstream transit node and is calculated using measured link blocking probabilities at each downstream transit node. The selection priority of each outgoing link is given dynamically based on its expected route distance toward a destination node. By considering the possibility of contention at downstream nodes, a routing scheme with high performance can be realized. The loss rate of optical bursts is improved when an imbalanced load is applied to the network, and the loss rate of optical bursts is also improved when the network includes links with extremely different distances.

This paper proposes the design to reduce the number of fed elements by replacing with parasitic elements in an array antenna. The study depends on the analysis of electromagnetic wave fields in consideration of the coupling between the half-wavelength dipoles. The case of 2 fed elements and 2 parasitic elements is considered as a unit cell to form the total array. After optimizing the element arrangement, the antenna gain can match that of the equivalent 4-fed element case. Feeding networks in a high power radiating system are analyzed in terms of the length and matching of feed lines, and the arrangement of amplifiers.

Adaptive Virtual Queue (AVQ) introduces a novel implementation algorithm for Active Queue Management (AQM). The stability criterion for AVQ was deduced in literature [1], but it lacks practicability due to the difficulty of solving the transcendental equation. In this letter, the AVQ stability is further investigated based on the characteristic roots of delay-differential equation. Another stability criterion explicitly associated with parameters of network configuration is deduced and the upper bound of delay time for stable AVQ algorithm is determined. Finally, the conclusion is validated through simulation experiments.

ERS-1/2 wind scatterometers (WSC) data sets may contain cells in which two, instead of three, measurements are available. These data sets are called incomplete. Operational inversion procedures discard such data sets and therefore no wind field is estimated. This is very limiting in semi-closed seas such as the Mediterranean Sea. In this paper we propose a new inversion procedure capable to retrieving near surface wind fields from incomplete data sets. This procedure is an enhancement of an algorithm already proposed and tested by the authors. A set of comprehensive experiments are presented and discussed. It is shown that the inversion procedure gets to remarkable results even in presence of a large number of doublets.

An estimation method of source location of undesired electromagnetic wave from electronic devices by using the MUSIC algorithm is proposed. The MUSIC algorithm can estimate the direction of arrival accurately, however, the estimation error is large in the case of short range multiple coherent sources. In order to overcome this problem, a method to improve the estimation accuracy is presented. Experimental results show that the proposed method can reduce the maximum estimation error from 7 cm of the conventional method to 2 cm.

The performance of integrated segmentation and recognition of handwritten numeral strings relies on the classification accuracy and the non-character resistance of the underlying character classifier, which is variable depending on the techniques of pattern normalization, feature extraction, and classifier structure. In this paper, we evaluate the effects of 12 normalization functions and four selected feature types on numeral string recognition. Slant correction (deslant) is combined with the normalization functions and features so as to create 96 feature vectors, which are classified using two classifier structures. In experiments on numeral string images of the NIST Special Database 19, the classifiers have yielded very high string recognition accuracies. We show the superiority of moment normalization with adaptive aspect ratio mapping and the gradient direction feature, and observed that slant correction is beneficial to string recognition when combined with good normalization methods.

The scaled down feature size and the increased frequency of today's deep sub-micron region call for fundamental changes in driver-load models. To be more specific, new driver-load models need to take into consideration the nonlinear behavior of the drivers, the inductance effects of the loads, and the slew rates of the output waveforms. Current driver-load models use the conventional single Ceff (one-ramp) approach and treat the interconnect load as lumped RC networks. Neither the nonlinear property nor the inductance effects were considered. The accuracy of these existing models is therefore questionable. This paper introduces a new multi-ramp driver model that represents the interconnect load as a distributed RLC network. The employed two effective capacitance values capture the nonlinear behavior of the driver. The lossy transmission line approach accounts for the impact of inductance when modeling the driving point interconnect load. The new model shows improvements of 9% in the average delay error and 2.2% in the slew rate error compared to SPICE.

Change detection methods are used to detect changes between two frames in an image sequence. Fundamental techniques for detecting changes use a difference image between the two frames. The change of each pixel is detected if difference values exceed a pre-set threshold, which is determined on the basis of the estimated value of the variance of noises on the frames. Not only the noises on the frames but also illumination changes between the frames are critical problems for change detection. A recently proposed approach gives a threshold derived from the average of the difference image over areas which are estimated as non-change parts. However, such a threshold may not be appropriate since the approach uses no physical parameters such as light sources, the reflection of objects. This paper proposes a new change detection method based on a physical model, which describes physical parameters such as light sources and the reflection of objects, known as an illumination model. First, we show the derivation of a new threshold based on the illumination model. The threshold is derived from the angle of the light of sources, the gray level of background objects, and the normal-vector of the background objects. A new change detection algorithm using such a threshold is shown. Next, we show experimental results and comparison, in which the proposed method improves the accuracy of detection results, compared to change detection by using the conventional threshold. We also give discussion on the features of the proposed method.