In reconstructing 3-D from images based on feature points, one usually defines a triangular mesh that has these feature points as vertices and displays the scene as a polyhedron. If the scene itself is a polyhedron, however, some of the displayed edges may be inconsistent with the true shape. This paper presents a new technique for automatically eliminating such inconsistencies by using a special template. We also present a technique for removing spurious occluding edges. All the procedures do not require any thresholds to be adjusted. Using real images, we demonstrate that our method has high capability to correct inconsistencies.

Anycast refers to the transmission of data from a source node to (any) one member in the group of designed recipients in a network. When the physical network and the set of anycast requests are given, the Anycast Routing and Wavelength Assignment (ARWA) problem is to find a set of light-paths, one for each source, for anycasting messages to any one of the member in the anycast destination group such that not any path using the same wavelength passes through the same link. The goal of the ARWA problem is to minimize the number of used wavelengths. In this paper, the ARWA problem is formulated and studied; since ARWA problem is NP-hard, a three-phase genetic algorithm is proposed to solve it. This algorithm is used to find the close-to-optimal solution. Simulated results show that the proposed algorithm is able to achieve good performance.

In this paper, a multi-Gbps pre-emphasis design methodology and circuits for a 4/2 Pulse Amplitude Modulation (PAM) transmitter of high-speed data serial link over cable are proposed. Theoretically analysis of the total frequency response including pre-emphasis, package, cable loss and termination are first carried out. In order to gain higher data rates without increasing of symbol rate, we use 4 PAM in our system. Then, we propose a pre-emphasis architecture and algorithm that can enlarge the high frequency response so the overall frequency response in the receiver side is uniform within the desired frequency range. The overall circuit is implemented in TSMC 0.18 µm 1P6M 1.8 V CMOS process. A test chip of this transmitter with pre-emphasis, PLL circuit and on-chip termination resistors is implemented by full custom flow to verify the design methodology. The measurement results of 10/5 Gbps (4/2 PAM) are carried out over 5 meter (m) long cable and is in agreement with our analysis and simulation results.

This paper describes a sophisticated method to estimate visual direction using iris contours. This method requires only one monocular image taken by a camera with unknown focal length. In order to estimate the visual direction, we assume the visual directions of both eyes are parallel and iris boundaries are circles in 3D space. In this case, the two planes where the iris boundaries reside are also parallel. We estimate the normal vector of the two planes from the iris contours extracted from an input image by using an extended "two-circle" algorithm. Unlike most existing gaze estimation algorithms that require information about eye corners and heuristic knowledge about 3D structure of the eye in addition to the iris contours, our method uses two iris contours only. Another contribution of our method is the ability of estimating the focal length of the camera. It allows one to use a zoom lens to take images and the focal length can be adjusted at any time. The extensive experiments over simulated images and real images demonstrate the robustness and the effectiveness of our method.

The state-oriented design of IP multicast may lead to the scalability problem, especially when there is a very large number of concurrent multicast groups in the network. Motivated by this problem, explicit multicast offers a stateless design using header space of multicast data packets. In this paper, we propose a novel stateless scheme called Linkcast that efficiently eliminates processing overhead of explicit multicast protocols. In Linkcast, the multicast sender encodes the tree listing its links in a proper way. The tree code is sent with every multicast data packet. Simulation results and experiments with real-trees show that Linkcast completely eliminates processing overhead of other explicit multicast protocols such as Xcast with comparable header size overhead.

We research on an importance sampling (IS) simulation to estimate a low error probability of turbo codes. The simulation time reduction in IS depends on another probability density function (p.d.f.) called simulation p.d.f. The previous IS simulation method can not evaluate the error probability on the low SNR and waterfall region. We derive the optimal simulation p.d.f. which gives the perfect estimator. A new simulation p.d.f. design, which is related to the optimal one, is proposed to overcome the problem of the previous IS method. The proposed IS simulation can evaluate all possible error patterns. Finally, some computer simulations show that the proposed method can evaluate the error probability on the low SNR, waterfall, and error floor regions. At the evaluation of the BER of 10-7, the simulation time of the proposed method is about 1/350 times as short as that of the Monte-Carlo simulation. When the BER is less than 710-8, the proposed method requires shorter simulation time than the conventional IS method.

We define discretized Markov transformations and find an algorithm to give the number of maximal-period sequences based on discretized Markov transformations. In this report, we focus on the discretized dyadic transformations and the discretized golden mean transformations. Then we find an algorithm to give the number of maximal-period sequences based on these discretized transformations. Moreover, we define a number-theoretic function related to the numbers of maximal-period sequences based on these discretized transformations. We also introduce the entropy of the maximal-period sequences based on these discretized transformations.

We present a new method to detect weak linear frequency modulated (LFM) signals in strong noise using the chaos oscillator. Chaotic systems are sensitive to specific signals yet immune to noise. With our new method we firstly use the Radon-Wigner transform to dechirp the LFM signal. Secondly, we set up a chaotic oscillator sensitive to weak signals based on the Duffing equation, and poising the system at its critical state. Finally, we input the dechirped sequence into the system as a perturbation of the driving force. A weak signal with the same frequency will lead to a qualitative transition in the system state. The weak signal in the presence of strong noise can then be detected from the phase transition of the phase plane trajectory of the chaotic system. Computer simulation results show that LFM signals with an SNR lower than -27 dB can be detected by this method.

We present an efficient method to optimize network resource allocations under nonlinear Quality of Service (QoS) constraints. We first propose a suite of generalized proportional allocation schemes that can be obtained by minimizing the information-theoretic function of relative entropy. We then optimize over the allocation parameters, which are usually design variables an engineer can directly vary, either for a particular user or for the worst-case user, under constraints that lower bound the allocated resources for all other users. Despite the nonlinearity in the objective and constraints, we show this suite of resource allocation optimization can be efficiently solved for global optimality through a convex optimization technique called geometric programming. This general method and its extensions are applicable to a wide array of resource allocation problems, including processor sharing, congestion control, admission control, and wireless network power control.

We studied 10 Gbit/s-based time-spreading and wave-length-hopping (TS-WH) optical code division multiplexing (OCDM) using fiber Bragg gratings (FBGs). To apply it to such the high bit rate system more than ten gigabit, two techniques are adopted. One is encoding with the maximum spreading time of 400 ps, which is four times as data bit duration, to encode without shortening chip duration. Another is encoder design. The apodized refractive index profile to the unit-gratings composing the encoder is designed to encode the pulses with 10-20 ps width at 10 Gbit/s rate. Using these techniques, 210 Gbit/s OCDM is demonstrated successfully. In this scheme, transmission distance is limited due to dispersion effect because the signal has wide bandwidth to assign a wavelength-hopping pattern. We use no additional devices to compensate the dispersion, in order to construct simple and cost-effective system. Novel FBG encoder is designed to incorporate both encoding and compensating of group delay among chip pulses within one device. We confirm the extension of transmission distance in the TS-WH OCDM from the demonstration over 40 km-long single mode fiber.

It is known that in a bit-interleaved coded-modulation with iterative decoding (BICM-ID), signal constellation and mapping strongly influence the system's error performance. This letter presents good mappings of various 8-ary constellations for BICM-ID systems operating over a frequency non-selective block Rayleigh fading channel. Simulation results for the error performance of different constellations/mappings are also provided and discussed.

This paper presents a novel method of structure selection and identification for Hammerstein type nonlinear systems. An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The connection coefficients of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. The adjusting parameters for the ACF model structure, i.e. the number and widths of the subdomains and the shape of the ACF are properly selected by using a genetic algorithm, in which the Akaike information criterion is utilized as the fitness value function. The effectiveness of the proposed method is confirmed through numerical experiments.

This paper proposes homogeneous neural networks (HNNs), in which each neuron has identical weights. HNNs can realize shift-invariant associative memory, that is, HNNs can associate not only a memorized pattern but also its shifted ones. The transition property of HNNs is analyzed by the statistical method. We show the probability that each neuron outputs correctly and the error-correcting ability. Further, we show that HNNs cannot memorize over the number,, of patterns, where m is the number of neurons and k is the order of connections.

A new detection methodology for both of the core and the delta of the fingerprint using the extended relational graph is presented. This paper shows the way to detect both of the core loop and the delta loop from the extended relational graph, which we proposed in order to summarize the global feature of the fingerprint ridge pattern distribution. The experimental results for 180 fingerprint samples show that the processing time is ranging from 0.34 [sec] to 0.44 [sec] for each fingerprint image by using Pentium 4 1.8 GHz Processor. In our experiments, the core and the delta were successfully extracted in 94.4% of the 180 samples.

In this paper we are concerned with designing an extremum seeking control law for nonlinear systems. This is a modification of a standard extremum seeking controller. It is equipped with an accelerator to the original one aimed at achieving the maximum operating point more rapidly. This accelerator is designed by making use of a polynomial identification of an uncertain output map, the Butterworth filter to smoothen the control, and analog-digital converters. Numerical experiments show how this modified approach can be well in control of the Monod model of bioreactors.

Grid computing is a state-of-the-art parallel computing technology which enables worldwide computers to dynamically share their computing powers and resource to each other. The grid takes advantage of Internet as a universal communication platform to carry messages. Basically, Internet doesn't guarantee loss-free and ordered transmission, hence, the grid should keep the cause and effect of events by itself to ensure the correct ordering of command invocations at the remote hosts. The ordering issue arises when the messages travel across the networks with unpredictable delay. Recent research has studied the security and resource control issues, but failed to address the requirements of transport layer on the grid communication platform. In this paper, we propose the Causal Ordered Grid (COG) architecture and implement it to study the transport performance issues when the grid is built over worldwide networks. The COG provides a novel service model to the applications with time-sensitive and causal-ordered transportation. From our experiments, the design of the grid middleware should use a causal-ordered, time-sensitive transportation rather than TCP. Our research will be beneficial to the improvement of the grid computing and can provide wealthy empirical results for the designer.

We analyze the noise sensitivity of the focal length computation, the principal point estimation, and the orthogonality enforcement for single-view 3-D reconstruction based on vanishing points and orthogonality. We point out that due to the nonlinearity of the problem the standard statistical optimization is not very effective. We present a practical compromise for avoiding the computational failure and preserving high accuracy, allowing a consistent 3-D shape in the presence of however large noise.

To develop human interfaces such as home information equipment, highly capable word learning ability is required. In particular, in order to realize user-customized and situation-dependent interaction using language, a function is needed that can build new categories online in response to presented objects for an advanced human interface. However, at present, there are few basic studies focusing on the purpose of language acquisition with category formation. In this study, taking hints from an analogy between machine learning and infant developmental word acquisition, we propose a taxonomy-based word-learning model using a neural network. Through computer simulations, we show that our model can build categories and find the name of an object based on categorization.

A novel digital redesign methodology based on evolutionary programming (EP) is introduced to find the 'best' digital controller for optimal tracking design of hybrid uncertain multi-input/ multi-output (MIMO) input-delay systems with constraints on states and controls. To deal with these multivariable concurrent specifications and system restrictions, instead of conventional interval methods, the proposed global optimization scheme is able to practically implement optimal digital controller for constrained uncertain hybrid systems with input time delay. Further, an illustrative example is included to demonstrate the efficiency of the proposed method.

We propose a DOA-Matrix based blind CFO estimation method for a MIMO-OFDM system with Virtual Carriers. The method estimates CFO in closed-form by jointly exploiting the shift-invariant structure of time-domain signal received on multiple receive antennas. In contrast to previous training-based methods, the proposed method is bandwidth efficiency. We also present numerical simulation results for different transmit and receive antenna configurations and for different record lengths.