991 resultados para Préville, 1721-1799.


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How can one compute qualitative properties of the optical flow, such as expansion or rotation, in a way which is robust and invariant to the position of the focus of expansion or the center of rotation? We suggest a particularly simple algorithm, well-suited to VLSI implementations, that exploits well-known relations between the integral and differential properties of vector fields and their linear behaviour near singularities.

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Both multilayer perceptrons (MLP) and Generalized Radial Basis Functions (GRBF) have good approximation properties, theoretically and experimentally. Are they related? The main point of this paper is to show that for normalized inputs, multilayer perceptron networks are radial function networks (albeit with a non-standard radial function). This provides an interpretation of the weights w as centers t of the radial function network, and therefore as equivalent to templates. This insight may be useful for practical applications, including better initialization procedures for MLP. In the remainder of the paper, we discuss the relation between the radial functions that correspond to the sigmoid for normalized inputs and well-behaved radial basis functions, such as the Gaussian. In particular, we observe that the radial function associated with the sigmoid is an activation function that is good approximation to Gaussian basis functions for a range of values of the bias parameter. The implication is that a MLP network can always simulate a Gaussian GRBF network (with the same number of units but less parameters); the converse is true only for certain values of the bias parameter. Numerical experiments indicate that this constraint is not always satisfied in practice by MLP networks trained with backpropagation. Multiscale GRBF networks, on the other hand, can approximate MLP networks with a similar number of parameters.

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A fundamental understanding of the information carrying capacity of optical channels requires the signal and physical channel to be modeled quantum mechanically. This thesis considers the problems of distributing multi-party quantum entanglement to distant users in a quantum communication system and determining the ability of quantum optical channels to reliably transmit information. A recent proposal for a quantum communication architecture that realizes long-distance, high-fidelity qubit teleportation is reviewed. Previous work on this communication architecture is extended in two primary ways. First, models are developed for assessing the effects of amplitude, phase, and frequency errors in the entanglement source of polarization-entangled photons, as well as fiber loss and imperfect polarization restoration, on the throughput and fidelity of the system. Second, an error model is derived for an extension of this communication architecture that allows for the production and storage of three-party entangled Greenberger-Horne-Zeilinger states. A performance analysis of the quantum communication architecture in qubit teleportation and quantum secret sharing communication protocols is presented. Recent work on determining the channel capacity of optical channels is extended in several ways. Classical capacity is derived for a class of Gaussian Bosonic channels representing the quantum version of classical colored Gaussian-noise channels. The proof is strongly mo- tivated by the standard technique of whitening Gaussian noise used in classical information theory. Minimum output entropy problems related to these channel capacity derivations are also studied. These single-user Bosonic capacity results are extended to a multi-user scenario by deriving capacity regions for single-mode and wideband coherent-state multiple access channels. An even larger capacity region is obtained when the transmitters use non- classical Gaussian states, and an outer bound on the ultimate capacity region is presented

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This research is concerned with the development of tactual displays to supplement the information available through lipreading. Because voicing carries a high informational load in speech and is not well transmitted through lipreading, the efforts are focused on providing tactual displays of voicing to supplement the information available on the lips of the talker. This research includes exploration of 1) signal-processing schemes to extract information about voicing from the acoustic speech signal, 2) methods of displaying this information through a multi-finger tactual display, and 3) perceptual evaluations of voicing reception through the tactual display alone (T), lipreading alone (L), and the combined condition (L+T). Signal processing for the extraction of voicing information used amplitude-envelope signals derived from filtered bands of speech (i.e., envelopes derived from a lowpass-filtered band at 350 Hz and from a highpass-filtered band at 3000 Hz). Acoustic measurements made on the envelope signals of a set of 16 initial consonants represented through multiple tokens of C1VC2 syllables indicate that the onset-timing difference between the low- and high-frequency envelopes (EOA: envelope-onset asynchrony) provides a reliable and robust cue for distinguishing voiced from voiceless consonants. This acoustic cue was presented through a two-finger tactual display such that the envelope of the high-frequency band was used to modulate a 250-Hz carrier signal delivered to the index finger (250-I) and the envelope of the low-frequency band was used to modulate a 50-Hz carrier delivered to the thumb (50T). The temporal-onset order threshold for these two signals, measured with roving signal amplitude and duration, averaged 34 msec, sufficiently small for use of the EOA cue. Perceptual evaluations of the tactual display of EOA with speech signal indicated: 1) that the cue was highly effective for discrimination of pairs of voicing contrasts; 2) that the identification of 16 consonants was improved by roughly 15 percentage points with the addition of the tactual cue over L alone; and 3) that no improvements in L+T over L were observed for reception of words in sentences, indicating the need for further training on this task

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Computers and Thought are the two categories that together define Artificial Intelligence as a discipline. It is generally accepted that work in Artificial Intelligence over the last thirty years has had a strong influence on aspects of computer architectures. In this paper we also make the converse claim; that the state of computer architecture has been a strong influence on our models of thought. The Von Neumann model of computation has lead Artificial Intelligence in particular directions. Intelligence in biological systems is completely different. Recent work in behavior-based Artificial Intelligenge has produced new models of intelligence that are much closer in spirit to biological systems. The non-Von Neumann computational models they use share many characteristics with biological computation.

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We present a model for recovering the direction of heading of an observer who is moving relative to a scene that may contain self-moving objects. The model builds upon an algorithm proposed by Rieger and Lawton (1985), which is based on earlier work by Longuet-Higgens and Prazdny (1981). The algorithm uses velocity differences computed in regions of high depth variation to estimate the location of the focus of expansion, which indicates the observer's heading direction. We relate the behavior of the proposed model to psychophysical observations regarding the ability of human observers to judge their heading direction, and show how the model can cope with self-moving objects in the environment. We also discuss this model in the broader context of a navigational system that performs tasks requiring rapid sensing and response through the interaction of simple task-specific routines.

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Different approaches to visual object recognition can be divided into two general classes: model-based vs. non model-based schemes. In this paper we establish some limitation on the class of non model-based recognition schemes. We show that every function that is invariant to viewing position of all objects is the trivial (constant) function. It follows that every consistent recognition scheme for recognizing all 3-D objects must in general be model based. The result is extended to recognition schemes that are imperfect (allowed to make mistakes) or restricted to certain classes of objects.

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We describe the automatic synthesis of a global nonlinear controller for stabilizing a magnetic levitation system. The synthesized control system can stabilize the maglev vehicle with large initial displacements from an equilibrium, and possesses a much larger operating region than the classical linear feedback design for the same system. The controller is automatically synthesized by a suite of computational tools. This work demonstrates that the difficult control synthesis task can be automated, using programs that actively exploit knowledge of nonlinear dynamics and state space and combine powerful numerical and symbolic computations with spatial-reasoning techniques.

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This thesis introduces elements of a theory of design activity and a computational framework for developing design systems. The theory stresses the opportunistic nature of designing and the complementary roles of focus and distraction, the interdependence of evaluation and generation, the multiplicity of ways of seeing over the history of a design session versus the exclusivity of a given way of seeing over an arbitrarily short period, and the incommensurability of criteria used to evaluate a design. The thesis argues for a principle based rather than rule based approach to designing documents. The Discursive Generator is presented as a computational framework for implementing specific design systems, and a simple system for arranging blocks according to a set of formal principles is developed by way of illustration. Both shape grammars and constraint based systems are used to contrast current trends in design automation with the discursive approach advocated in the thesis. The Discursive Generator is shown to have some important properties lacking in other types of systems, such as dynamism, robustness and the ability to deal with partial designs. When studied in terms of a search metaphor, the Discursive Generator is shown to exhibit behavior which is radically different from some traditional search techniques, and to avoid some of the well-known difficulties associated with them.

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This paper presents a model for the general flow in the neocortex. The basic process, called "sequence-seeking," is a search for a sequence of mappings or transformations, linking source and target representations. The search is bi-directional, "bottom-up" as well as "top-down," and it explores in parallel a large numbe rof alternative sequences. This operation is implemented in a structure termed "counter streams," in which multiple sequences are explored along two separate, complementary pathways which seeking to meet. The first part of the paper discusses the general sequence-seeking scheme and a number of related processes, such as the learning of successful sequences, context effects, and the use of "express lines" and partial matches. The second part discusses biological implications of the model in terms of connections within and between cortical areas. The model is compared with existing data, and a number of new predictions are proposed.

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I have previously described psychophysical experiments that involved the perception of many transparent layers, corresponding to multiple matching, in doubly ambiguous random dot stereograms. Additional experiments are described in the first part of this paper. In one experiment, subjects were required to report the density of dots on each transparent layer. In another experiment, the minimal density of dots on each layer, which is required for the subjects to perceive it as a distinct transparent layer, was measured. The difficulties encountered by stereo matching algorithms, when applied to doubly ambiguous stereograms, are described in the second part of this paper. Algorithms that can be modified to perform consistently with human perception, and the constraints imposed on their parameters by human perception, are discussed.

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We address the computational role that the construction of a complete surface representation may play in the recovery of 3--D structure from motion. We present a model that combines a feature--based structure--from- -motion algorithm with smooth surface interpolation. This model can represent multiple surfaces in a given viewing direction, incorporates surface constraints from object boundaries, and groups image features using their 2--D image motion. Computer simulations relate the model's behavior to perceptual observations. In a companion paper, we discuss further perceptual experiments regarding the role of surface reconstruction in the human recovery of 3--D structure from motion.

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This paper describes a theory of inheritance theories. We present an original theory of inheritance in nonmonotonic hierarchies. The structures on which this theory is based delineate a framework that subsumes most inheritance theories in the literature, providing a new foundation for inheritance. * Our path-based theory is sound and complete w.r.t. a direct model-theoretic semantics. * Both the credulous and the skeptical conclusions of this theory are polynomial-time computable. * We prove that true skeptical inheritance is not contained in the language of path-based inheritance. Because our techniques are modular w.r.t. the definition of specificity, they generalize to provide a unified framework for a broad class of inheritance theories. By describing multiple inheritance theories in the same "language" of credulous extensions, we make principled comparisons rather than the ad-hoc examination of specific examples makes up most of the comparative inheritance work.

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We present a novel ridge detector that finds ridges on vector fields. It is designed to automatically find the right scale of a ridge even in the presence of noise, multiple steps and narrow valleys. One of the key features of such ridge detector is that it has a zero response at discontinuities. The ridge detector can be applied to scalar and vector quantities such as color. We also present a parallel perceptual organization scheme based on such ridge detector that works without edges; in addition to perceptual groups, the scheme computes potential focus of attention points at which to direct future processing. The relation to human perception and several theoretical findings supporting the scheme are presented. We also show results of a Connection Machine implementation of the scheme for perceptual organization (without edges) using color.

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We have simulated numerically an automated Maxwell's demon inspired by Smoluchowski's ideas of 1912. Two gas chambers of equal area are connected via an opening that is covered by a trapdoor. The trapdoor can open to the left but not to the right, and is intended to rectify naturally occurring variations in density between the two chambers. Our results confirm that though the trapdoor behaves as a rectifier when large density differences are imposed by external means, it can not extract useful work from the thermal motion of the molecules when left on its own.