846 resultados para robust speaker verification


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Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

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We use robust semidefinite programs and entanglement witnesses to study the distillability of Werner states. We perform exact numerical calculations that show two-undistillability in a region of the state space, which was previously conjectured to be undistillable. We also introduce bases that yield interesting expressions for the distillability witnesses and for a tensor product of Werner states with an arbitrary number of copies.

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We consider a problem of robust performance analysis of linear discrete time varying systems on a bounded time interval. The system is represented in the state-space form. It is driven by a random input disturbance with imprecisely known probability distribution; this distributional uncertainty is described in terms of entropy. The worst-case performance of the system is quantified by its a-anisotropic norm. Computing the anisotropic norm is reduced to solving a set of difference Riccati and Lyapunov equations and a special form equation.

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The future role and structure of Australian general practice remains uncertain, despite a decade of seemingly constant change following the release of the National Health Strategy papers. Some of the suggested change strategies (such as rural Practice Incentive Payments and practice accreditation) have been implemented; others (such as general practitioner involvement with area health authorities in delivering national goals and targets for communities) still await attention. An overarching vision for our health care system in 2020 and general practice's role within it are still to be clearly enunciated. Australia is at variance with other Western countries, such as the United Kingdom, Canada and New Zealand, which have spent significant time refocusing their health systems to deal with an ageing population with an increased burden of chronic disease. Health bureaucrats and governments need to invest strategically in operational primary care now. This will require the active commitment of general practice's national bodies to articulate and actively promote a shared vision for Australian general practice.

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Proof reuse, or analogical reasoning, involves reusing the proof of a source theorem in the proof of a target conjecture. We have developed a method for proof reuse that is based on the generalisation replay paradigm described in the literature, in which a generalisation of the source proof is replayed to construct the target proof. In this paper, we describe the novel aspects of our method, which include a technique for producing more accurate source proof generalisations (using knowledge of the target goal), as well as a flexible replay strategy that allows the user to set various parameters to control the size and the shape of the search space. Finally, we report on the results of applying this method to a case study from the realm of software verification.

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It is not surprising that students are unconvinced about the benefits of formal methods if we do not show them how these methods can be integrated with other activities in the software lifecycle. In this paper, we describe an approach to integrating formal specification with more traditional verification and validation techniques in a course that teaches formal specification and specification-based testing. This is accomplished through a series of assignments on a single software component that involves specifying the component in Object-Z, validating that specification using inspection and a specification animation tool, and then testing an implementation of the specification using test cases derived from the formal specification.

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Despite decades of research, the takeup of formal methods for developing provably correct software in industry remains slow. One reason for this is the high cost of proof construction, an activity that, due to the complexity of the required proofs, is typically carried out using interactive theorem provers. In this paper we propose an agent-oriented architecture for interactive theorem proving with the aim of reducing the user interactions (and thus the cost) of constructing software verification proofs. We describe a prototype implementation of our architecture and discuss its application to a small, but non-trivial case study.

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One of critical challenges in automatic recognition of TV commercials is to generate a unique, robust and compact signature. Uniqueness indicates the ability to identify the similarity among the commercial video clips which may have slight content variation. Robustness means the ability to match commercial video clips containing the same content but probably with different digitalization/encoding, some noise data, and/or transmission and recording distortion. Efficiency is about the capability of effectively matching commercial video sequences with a low computation cost and storage overhead. In this paper, we present a binary signature based method, which meets all the three criteria above, by combining the techniques of ordinal and color measurements. Experimental results on a real large commercial video database show that our novel approach delivers a significantly better performance comparing to the existing methods.