The goal of this paper is to present a critical survey of existing literature on an omnidirectional sensing. The area of vision application such as autonomous robot navigation, telepresence and virtual reality is expanding by use of a camera with a wide angle of view. In particular, a real-time omnidirectional camera with a single center of projection is suitable for analyzing and monitoring, because we can easily generate any desired image projected on any designated image plane, such as a pure perspective image or a panoramic image, from the omnidirectional input image. In this paper, I review designs and principles of existing omnidirectional cameras, which can acquire an omnidirectional (360 degrees) field of view, and their applications in fields of autonomous robot navigation, telepresence, remote surveillance and virtual reality.

Optimum filters for an image restoration are formed by a degradation operator, a covariance operator of original images, and one of noise. However, in a practical image restoration problem, the degradation operator and the covariance operators are estimated on the basis of empirical knowledge. Thus, it appears that they differ from the true ones. When we restore a degraded image by an optimum filter belonging to the family of Projection Filters and Parametric Projection Filters, it is shown that small deviations in the degradation operator and the covariance matrix can cause a large deviation in a restored image. In this paper, we propose new optimum filters based on the regularization method called the family of Regularized Projection Filters, and show that they are stable to deviations in operators. Moreover, some numerical examples follow to confirm that our description is valid.

Effects of the model order estimation error in the TLS-ESPRIT algorithm were investigated. It was found that if the model order is overestimated true signal parameters are preserved even though spurious signals of which power values are negligibly small appear, whereas if the model order is underestimated some signals degenerate to each others, resulting in the erroneous estimates.

An unbiased estimation method for symmetric noncausal ARMA model parameters is presented. The proposed algorithm works in two steps: first, a spectrally equivalent causal system is identified by lattice whitening filter and then the equivalent noncausal system is reconstructed. For AR system with noise or ARMA system without noise, the proposed method does not need any iteration method nor any optimization procedure. An estimation method of noise variance when the observation is made in noisy situation is discussed. The potential capabilities of the algorithm are demonstrated by using some numerical examples.

In this paper, we present an efficient approach for technology scaling of MOS analog circuits by using circuit optimization techniques. Our new method is based on matching equivalent circuit parameters between a previously designed circuit and the circuit undergoing redesign. This method has been applied to a MOS operational amplifier. We were able to produce a redesigned circuit with almost the same performance in under 4 hours, making this method 5 times more efficient than conventional methods

Speech signals transmitted over telephone network often suffer from interference due to ambient noise and channel distortion. In this paper, a novel frame-dependent fuzzy channel compensation (FD-FCC) method employing two-stage bias subtraction is proposed to minimize the channel effect. First, through maximum likelihood (ML) estimation over the set of all word models, we choose the word model which is best matched with the input utterance. Then, based upon this word model, a set of mixture biases can be derived by averaging the cepstral differences between the input utterance and the chosen model. In the second stage, instead of using a single bias, a frame-dependent bias is calculated for each input frame to equalize the channel variations in the input utterance. This frame-dependent bias is achieved by the convex combination of those mixture biases which are weighted by a fuzzy membership function. Experimental results show that the channel effect can be effectively canceled even though the additive background noise is involved in a telephone speech recognition system.

A Multi-Agent Learning Language (MALL) is defined as being necessary for agents in environments where they encounter crucial situations in which they have to learn about the environment, other parties moves and strategies, and then construct an optimal plan. The language is based on two major factors, the level of certainty in fully monitoring (surveying) the agents and the environment, and optimal plan construction, in an autonomous way. Most of the work related to software agents is based on the assumption that other agents are trustworthy. In the growing Internet environment this may not be true. The proposed new learning language allows agents to learn about the environment and the strategies of their opponents while devising their own plans. The language is being tested in our project of software agents for Electronic Commerce that operates in various security zones. The language is flexible and adaptable to a variety of agents applications.

In ATM Network, the VBR (Variable Bit Rate) service category is used to accommodate TCP/IP traffic. In an international ATM network with large propagation delay, higher TCP throughput can be obtained by use of window scale option. In order to accommodate TCP traffic with window scale option effectively, it is required to select appropriate values of VBR parameters, i. e. SCR (Sustainable Cell Rate) and MBS (Maximum Burst Size), and to evaluate the impact of UPC (Usage Parameter Control) function on TCP throughput. We have studied those technical issues for the conventional TCP, but the results cannot be applied to TCP traffic with the window scale option due to the TCP terminal performance and the large window size. In this paper, we proposed VBR parameter determination method for TCP with the window scale option and evaluated the values in each condition. These results show that the determined MBS is much smaller than the burst length of TCP segments especially using low performance TCP terminals. Furthermore, we also discuss some experimental results of TCP throughput degradation due to UPC function. It shows that the throughput of TCP with large window size is degraded when the SCR and MBS values used in ATM switch are smaller than the determined values.

In the commonsense reasoning, priorities among rules are often required to be found out in order to derive the desired conclusion as a theorem of the reasoning. In this paper, first we present the bottom-up and top-down abduction procedures to compute skeptical explanations and secondly show that priorities of circumscription to infer a desired theorem can be abduced as a skeptical explanation in abduction. In our approach, the required priorities can be computed based on the procedure to compute skeptical explanations provided in this paper as well as Wakaki and Satoh's method of compiling circumscription into extended logic programs. The method, for example, enables us to automatically find the adequate priority w. r. t. the Yale Shooting Problem to express a human natural reasoning in the framework of circumscription.

We describe several properties of very thin stacks of 10 to 20 intrinsic Josephson junctions fabricated on the surface of Bi2Sr2CaCu2O8+δ single crystals. We show that the Joule heating is significantly reduced in these stacks and that the gap structure is clearly observable in the quasiparticle current-voltage (I-V) characteristics. The I-V curves are characterized by a large subgap conductance and a significant gap suppression due to the injection of quasiparticle current. It is found that the IcRn product of these intrinsic Josephson junction stacks is significantly small compared with that expected from the BCS theory. It is also found that there is a tendency that IcRn decreases with increasing c-axis resistivity. Both Ic and the gap voltage exhibit unsaturated temperature dependence at low temperatures. The behavior presents a sharp contrast to that of Josephson junctions made of conventional superconductors. The characteristics are discussed in relation to the d-wave symmetry of the order parameter.

We discuss the concept of coding over the ring of integers modulo m. This method of coding finds its origin in the early work by Varshamov and Tenengolz. We first give a definition of the codes followed by some general properties. We derive specific code constructions and show computer-search results. We conclude with applications in 8-phase modulation and peak-shift correction in magnetic recording systems.

Image restoration using estimated parameters of image model and noise statistics is presented. The image is modeled as the output of a 2-D noncausal autoregressive (NCAR) model. The parameter estimation process is done by using the autocorrelation function and a biased term to a conventional least-squares (LS) method for the noncausal modeling. It is shown that the proposed method gives better results than the other parameter estimation methods which ignore the presence of the noise in the observation data. An appropriate image model selection process is also presented. A genetic algorithm (GA) for solving a multiobjective function with single constraint is discussed.

This paper presents a new algorithm that can solve the problem of selecting appropriate update step size in the LMS algorithm. The proposed algorithm, called a Complementary Pair LMS (CP-LMS) algorithm, consists of two adaptive filters with different update step sizes operating in parallel, one filter re-initializing the other with the better coefficient estimates whenever possible. This new algorithm provides the faster convergence speed and the smaller steady-state error than those of a single filter with a fixed or variable step size.

From an information geometric viewpoint, we investigate a characteristic of the submanifold of a mixture or exponential family in the manifold of finite discrete distributions. Using the characteristic, we derive a direct calculation method for an em-geodesic in the submanifold. In this method, the value of the primal parameter on the geodesic can be obtained without iterations for a gradient system which represents the geodesic. We also derive the similar algorithms for both problems of parameter estimation and functional extension of the submanifold for a data in the ambient manifold. These theoretical approaches from geometric analysis will contribute to the development of an efficient algorithm in computational complexity.

The conventional method requires a centerline of a vessel to estimate the vessel diameter. Two methods of estimating the centerline of vessels have been reported: One is to manually define the centerline of the vessel. This potentially contributes to inter- and intra-observer variability. The orientation of the centerline has an effect on the diameter function since diameters are computed perpendicular to the centerline. And the other is to automatically detect the centerline of the vessel. But this is a very complicated method. In this paper, we propose a new method of estimating vessel diameter using direction codes without detecting centerline. Since this method detects the vessel boundary and direction code at the same time, it simplifies the procedure and reduces execution time in estimating the vessel diameter. Compared to a method that automatically estimates the vessel diameter using centerline, a proposed method provides an improved accuracy in image with poor contrast, branching or obstructed vessels. Also, this provides a good compression of boundary description. Our experiments demonstrate the usefulness of the technique using direction code for quantitative angiography. Experimental results justify the validity of the proposed method.

This paper proposes a fast scheduling algorithm based on gradual time-frame reduction for datapath synthesis of digital signal processing hardwares. The objective of the algorithm is to minimize the costs for functional units and registers and to maximize connectivity under given computation time and initiation interval. Incorporating the connectivity in a scheduling stage can reduce multiplexer counts in resource binding. The algorithm maximizes connectivity with maintaining low time complexity and obtains datapath designs with totally small hardware costs in the high-level synthesis environment. The algorithm also resolves inter-iteration data dependencies and thus realizes pipelined datapaths. The experimental results demonstrate that the proposed algorithm reduces the multiplexer counts after resource binding with maintaining low costs for functional units and registers compared with eight conventional schedulers.

The purpose of this letter is to investigate the stability conditions of the active two port networks having some restrictions on load and source terminations, and then they have been obtained. Next, these results and the previous stability coditions are investigated, and then the new combined stability condition are proposed.

This paper proves a general sampling theorem, which is an extension of Shannon's classical theorem. Let o be a closed subspace of square integrable functions and call o a signal space. The main aim of this paper is giving a necessary and sufficient condition for unique existence of the sampling basis {Sn}o without band-limited assumption. Using the general sampling theorem we rigorously discuss a frequency domain treatment and a general signal space spanned by translations of a single function. Many known sampling theorems in signal spaces, which have applications for multiresolution analysis in wavelets theory are corollaries of the general sampling theorem.

This paper describes a new high resolution algorithm for the two-dimensional (2-D) frequency estimation problem, which, in particular, is noise insensitive in view of the fact that in many practical applications the contaminated noise may not be white noise. For this purpose, the approach is set in the context of higher-order statistics (HOS), which has demonstrated to be an effective approach under a colored noise environment. The algorithm begins with the consideration of the fourth-order moments of the available 2-D data. Two auxiliary matrices, constituted by a novel stacking of the diagonal slice of the computed fourth-order moments, are then introduced and through which the two frequency components can be precisely determined, respectively, via matrix factorizations along with the subspace rotational invariance (SRI) technique. Simulation results are also provided to verify the proposed algorithm.

This paper deals with a set of differential operators for calculating the differentials of an observed signal by the Daubechies wavelet and its application for the estimation of the transfer function of a linear system by using non-stationary step-like signals. The differential operators are constructed by iterative projections of the differential of the scaling function for a multiresolution analysis into a dilation subspace. By the proposed differential operators we can extract the arbitrary order differentials of a signal. We propose a set of identifiable filters constructed by the sum of multiple filters with the first order lag characteristics. Using the above differentials and the identifiable filters we propose an identification method for the transfer function of a linear system. In order to ensure the appropriateness and effectiveness of the proposed method some numerical simulations are presented.