Reconstruction of polygonal sets by constrained and unconstrained double probing

The problem of recovering the shape of planar objects arises in robotics. This work deals with this problem under the assumption that composite double probings are made. Two kinds of double probes are considered and their use for reconstructing convex planar polygons is investigated. For both kinds of probes, lower bounds on the number of probings required for reconstruction under any strategy are obtained and specific strategies which are proven to be almost optimal are provided.     

A Lie group approach to a neural system for three-dimensionalinterpretation of visual motion

A novel approach is presented to neural network computation of three-dimensional rigid motion from noisy two-dimensional image flow. It is shown that the process of 3-D interpretation of image flow can be viewed as a linear signal transform. The elementary signals of this linear transform are the 2-D vector fields of the six infinitesimal generators of the 3-D Euclidean group. This transform can be performed by a neural network. Results are also reported of neural network simulations for the 3-D interpretation of image flow and a comparison of the performance of this approach with that using conventional methods. Computer simulation results verify the Lie-group-based neural network approach to three-dimensional motion perception.     

Recurrent correlation associative memories

A model for a class of high-capacity associative memories is presented. Since they are based on two-layer recurrent neural networks and their operations depend on the correlation measure, these associative memories are called recurrent correlation associative memories (RCAMs). The RCAMs are shown to be asymptotically stable in both synchronous and asynchronous (sequential) update modes as long as their weighting functions are continuous and monotone nondecreasing. In particular, a high-capacity RCAM named the exponential correlation associative memory (ECAM) is proposed. The asymptotic storage capacity of the ECAM scales exponentially with the length of memory patterns, and it meets the ultimate upper bound for the capacity of associative memories. The asymptotic storage capacity of the ECAM with limited dynamic range in its exponentiation nodes is found to be proportional to that dynamic range. Design and fabrication of a 3-mm CMOS ECAM chip is reported. The prototype chip can store 32 24-bit memory patterns, and its speed is higher than one associative recall operation every 3 mus. An application of the ECAM chip to vector quantization is also described.     

A real-time neural system for color constancy

A neural network approach to the problem of color constancy is presented. Various algorithms based on Land's retinex theory are discussed with respect to neurobiological parallels, computational efficiency, and suitability for VLSI implementation. The efficiency of one algorithm is improved by the application of resistive grids and is tested in computer simulations; the simulations make clear the strengths and weaknesses of the algorithm. A novel extension to the algorithm is developed to address its weaknesses. An electronic system that is based on the original algorithm and that operates at video rates was built using subthreshold analog CMOS VLSI resistive grids. The system displays color constancy abilities and qualitatively mimics aspects of human color perception.     

Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels

This paper presents and analyzes in detail an efficient search method based on evolutionary algorithms (EA) assisted by local Gaussian random field metamodels (GRFM). It is created for the use in optimization problems with one (or many) computationally expensive evaluation function(s). The role of GRFM is to predict objective function values for new candidate solutions by exploiting information recorded during previous evaluations. Moreover, GRFM are able to provide estimates of the confidence of their predictions. Predictions and their confidence intervals predicted by GRFM are used by the metamodel assisted EA. It selects the promising members in each generation and carries out exact, costly evaluations only for them. The extensive use of the uncertainty information of predictions for screening the candidate solutions makes it possible to significantly reduce the computational cost of singleand multiobjective EA. This is adequately demonstrated in this paper by means of mathematical test cases and a multipoint airfoil design in aerodynamics.     

International Working Group on Assurance Cases (for Security)

Critical systems are aptly named - from electric power to water and gas to the telephone system and the Internet, they're all critical to some aspect of our daily lives. We're a networked society and as such, it's important to both know whether critical systems are trustworthy and be able to communicate, review, and debate the level of trust achieved in them. In the safety domain, explicit safety cases are increasingly required by law, regulations, and standards. In this article, we outline what a small, international group of experts, spanning various disciplines in safety, security, reliability, and critical infrastructure, been doing with the International Working Group on Assurance Cases (for Security), what we hope to achieve, and where we go next.     

Performance engineering and topological design of metro WDM opticalnetworks using computer simulation

This paper demonstrates the use of computer simulation for topological design and performance engineering of transparent wavelength-division multiplexing metropolitan-area networks. Engineering of these networks involves the study of various transport-layer impairments such as amplifier noise, component ripple, chirp/dispersion, optical crosstalk, waveform distortion due to filter concatenation, fiber nonlinearities, and polarization effects. A computer simulation methodology composed of three main simulation steps is derived and implemented. This methodology obtains performance estimations by applying efficient wavelength-domain simulations on the entire network topology, followed by time-/frequency-domain simulations on selected paths of the network and finally Q-budgeting on an identified worst case path. The above technique provides an efficient tool for topological design and network performance engineering. Accurate simulation models are presented for each of the performance impairments, and the computer simulation methodology is used for the design and engineering of a number of actual metro network architectures