International Professional University of Technology in Nagoya Repository
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Phase Unmixing : Multichannel Source Separation with Magnitude Constraints
No full textInternational audienceWe consider the problem of estimating the phases of K mixed complex signals from a multichannel observation, when the mixing matrix and signal magnitudes are known. This problem can be cast as a non-convex quadratically constrained quadratic program which is known to be NP-hard in general. We propose three approaches to tackle it: a heuristic method, an alternate minimization method, and a convex relaxation into a semi-definite program. The last two approaches are showed to outperform the oracle multichannel Wiener filter in under-determined informed source separation tasks, using simulated and speech signals. The convex relaxation approach yields best results, including the potential for exact source separation in under-determined settings
Chaos-based Cryptography: a Promising Technology
No full textJournée GDR ISIS "Traitement et communication des images médicales" Université d’Evry Val d’Essonne, 23 mars 2017Security and confidentiality of image and video data is an important research topic and have been widely investigated by using standard cryptography and chaos-based cryptography. Indeed, a variety of chaos-based cryptosystems have been investigated during the last decade. Most of them are based on the structure of Fridrich, which is based on the traditional confusion-diffusion architecture proposed by Shannon. Compared with traditional cryptography, the chaos-based cryptography are more flexible which make them more suitable for large scale-data encryption, such as images and video. The heart of any chaos-based cryptosystem is the chaotic generator and so, a part of the efficiency (robustness, speed) of the system depends greatly on it. Furthermore, in stream ciphers all the security depend on the used pseudo-random number generator (PRNG).In this talk, we present two strong chaos-based cryptosystems: a stream cipher and block cipher. These chaos- cryptosystems are recently published
Identification and control of nonlinear electro-mechanical systems
No full textEditorial of the special issue : Identification and Control of Nonlinear Electro-Mechanical SystemsInternational audienceElectro-mechanical systems are systems composed of both electrical and mechanical parts. They include motors, robots, cranes, compactors, electro-mechanical positioning systems, nanopositioning systems, and piezoelectric actuators, amongst others. As a consequence, mechanical and electrical engineering communities encompass a variety of fields such as robotics, mechatronics, electrotechnics, electronics, and power engineering, all of which can be considered a part of an over-arching electro-mechanical community.Within the electro-mechanical community, system identification refers to the whole process of identifying the most appropriate model form and estimating the parameters of this model from measured input/output data or from a combination of such data and prior knowledge. Dynamical models obtained in this manner are useful for tasks such as analysing the system properties (e.g. identification of nonlinear friction models); performing simulation experiments; and control system design (e.g. model-based control, predictive control, sliding-mode control).Such dynamical models are usually formulated in terms of differential equations, or transfer functions in the differential operator, because the physical laws on which the models are based are normally synthesised in terms of differential equation relationships based on natural laws, such as Newton's laws, Ohm's law, Kirchhoff's relations and Maxwell's equations. It is not surprising, therefore, that most electro-mechanical engineering theory and practice is based on continuous-time models. Electro-mechanical system control has similar objectives to most automatic control systems, i.e. to control the system so that its output follows a desired reference, which may be a fixed or changing value (a set point or trajectory).Despite the similarities between the automatic control and electro-mechanical engineering communities, some important differences remain. For example, within the electro-mechanical community, the identification and/or control methodology is mostly devoted to specific real-world systems rather than to general systems. The theoretical aspects of methodology, such as the statistical efficiency of the model parameter estimates or the optimality of the control system, are addressed much less often, whereas these are prolific topics in the automatic control community, where many papers are based on theoretical analysis and results. The electro-mechanical community, on the other hand, is often more reluctant to make general theoretical assumptions, tending to mistrust such generalisations when dealing with real-world systems and producing experimental results. And finally, both nonlinearity and high dimensionality are often unavoidable in electro-mechanical systems and so the consideration of such factors is much more prevalent in the electro-mechanical engineering community.Fortunately, there is evidence that these differences between the two communities are growing less and the present special issue is intended to encourage still greater cross-fertilisation between the communities, which we believe will result in advantages to both. It presents papers dealing with examples that are concerned with the identification and control of various different electro-mechanical systems; and examples that help to reveal the capabilities of current identification/control methods when they are applied to challenging, real-world applications.In the review of the content below, the papers have been separated into those that are involved with the implementation of the proposed methodology on a real electro-mechanical system, which are considered first, and then those that use computer simulation to demonstrate the feasibility of the proposed methodology
A Modified Enhanced Transmission Line Theory Applied to Multiconductor Transmission Lines
No full textInternational audienceIn this paper, a multiconductor modified enhanced transmission line theory is presented. The constitutive equations of this theory are directly derived from Maxwell's equations without the restriction to the transverse electromagnetic mode, while conserving the mathematical formalism of the classical transmission line theory (TLT). However, the per-unit-length (p.u.l.) parameters become complex and frequency dependent but still have an RLCG form. Besides, these new parameters are expressed as a combination of the classical ones and a high-frequency correction. These equations can be easily solved by the existing classical TLT solvers. The results obtained by this theory are in a much better agreement than the classical TLT with those predicted by a full-wave solver or measurements. © 2016 IEEE
Prediction of non-linear site response using downhole array data and numerical modeling: The Belleplaine (Guadeloupe) case study
No full textInternational audienceIn this study, we analyze the acceleration time histories data at the Belleplaine (Guadeloupe, French West Indies) vertical array, recorded between 2008 and 2014, to evaluate the seismic response of sediments. First, we apply seismic interferometry by deconvolution method to compute the in-situ shear wave velocity between the sensor at the surface and the two shallow sensors located at GL-15m and GL-39m depth. The efficiency of this method is discussed by studying the variability of the velocity profile obtained and comparing with the in-situ geophysical survey of the site. Computed strains between sensors remain very weak, lower than 10−5, meaning that nonlinearities are not expected for these events. Moreover, the small dispersion of shear wave velocities values deduced from seismic interferometry may be related to the elastic behavior of the soil column. Furthermore, the transfer functions between each sensor combination are inverted to obtain a new velocity profile compatible with the geological knowledge of the site. The lag times calculated by seismic interferometry are then used to constrain random perturbations of the inverted velocity profile, allowing to study the variability of the 1D soil response. Since recorded motion has a PGA less than 10 cm/s2 in the dataset, we numerically predict the nonlinear response of the site using strong motion from a worldwide dataset. Furthermore, we study the ratio between the PGV and the medium shear velocity as a proxy showing the development of shear deformation during strong motion. Finally, using strong motion events from a worldwide dataset, we numerically predict the nonlinear response of the site based on shear wave velocity variation and the strain proxy computed by the particle velocity versus shear wave velocity ratio. We conclude that seismic interferometry by deconvolution is a robust and accurate solution to help extracting the shear wave velocity profile and to monitor the soil nonlinear response. This technique can be used when strong earthquakes will be recorded at this experimental site in order to track and assess nonlinear effects in the soil column
Quantifying Conflicts in Propositional Logic Through Prime Implicates
No full textInternational audienceQuantifying conflicts is recognized as an important issue for handling inconsistencies. Indeed, an inconsistency measure can be employed to support knowledge engineers in building a consistent and usable knowledge base or providing insights on how to repair an inconsistent one. Good measures are supposed to satisfy a set of rational properties. However, defining sound properties is sometimes problematic. In this paper, we emphasize one such property, named dominance, rarely satisfied by syntactic measures. Based on prime implicates canonical representation, we first introduce the notion of conflicting variable and use it to refine an existing inconsistency measure defined by minimally unsatisfiable sets (MUSes). Then, we provide a semantics characterization allowing us to establish relationships with multi-valued semantics. Secondly, we propose a new measure based on the notion of deduced MUSes (DMUSes), to circumscribe the internal conflicts in a given knowledge base. We also prove that this measure satisfies a new but weaker form of dominance. Finally, we show how inconsistency measures based on hitting sets of minimal inconsistent sets can be extended using hitting sets of DMUSes
A consolidated perspective on multi-microphone speech enhancement and source separation
No full textAdded equation (108)International audienceSpeech enhancement and separation are core problems in audio signal processing, with commercial applications in devices as diverse as mobile phones, conference call systems, hands-free systems, or hearing aids. In addition, they are crucial pre-processing steps for noise-robust automatic speech and speaker recognition. Many devices now have two to eight microphones. The enhancement and separation capabilities offered by these multichannel interfaces are usually greater than those of single-channel interfaces. Research in speech enhancement and separation has followed two convergent paths, starting with microphone array processing and blind source separation, respectively. These communities are now strongly interrelated and routinely borrow ideas from each other. Yet, a comprehensive overview of the common foundations and the differences between these approaches is lacking at present. In this article, we propose to fill this gap by analyzing a large number of established and recent techniques according to four transverse axes: a) the acoustic impulse response model, b) the spatial filter design criterion, c) the parameter estimation algorithm, and d) optional postfiltering. We conclude this overview paper by providing a list of software and data resources and by discussing perspectives and future trends in the field
Energy-Efficient Downlink Resource Allocation in Heterogeneous OFDMA Networks
No full textInternational audienceIn this paper, we investigate energy-efficient downlink resource allocation in heterogeneous OFDMA networks, and formulate the energy efficiency (EE) maximization problem as a mixed-integer nonlinear fractional programming (MINLFP) problem with a non-concave nonlinear objective function and nonlinear constraints. By means of fractional programming and changing of variables, we transform the original MINLFP problem into an equivalent optimization problem in a parametric subtractive form, which is proved to be a concave mixed-integer nonlinear programming (MINLP) problem and is optimally solved by using Dinkelbach and branch-and-bound (BB) methods. In BB method, the concave MINLP problem is relaxed to a series of concave nonlinear programming problems and solved by the use of Powell-Hestenes-Rockafellar augmented Lagrangian method. The optimal solution can be used to benchmark the performance of sub-optimal solutions. As the computational complexity of BB method increases exponentially with problem size, we further develop a sub-optimal two-step scheme, which first allocates the resource blocks and then performs the transmit power control, to give sub-optimal solution with much lower complexity. Simulation results demonstrate the effectiveness of the proposed schemes and show that the proposed sub-optimal two-step scheme is promising for practical applications as it makes a good tradeoff between EE performance and computational complexity
Multicriteria Sorting with Category Size Restrictions
No full textInternational audienceWe consider the multi-criteria sorting problem where alternatives that are evaluated on multiple criteria are assigned into ordered categories. We focus on the sorting problem with category size restrictions, where the decision maker (DM) may have some concerns or constraints on the number of alternatives that should be assigned to some of the categories. We develop an approach based on the UTADIS method that fits an additive utility function to represent the decision maker’s preferences. We introduce additional variables and constraints to enforce the restrictions on the sizes of categories. The new formulation reduces the number of binary variables and hence decreases the computational effort compared to the existing approaches in the literature. We further improve the computational efficiency by developing lower and upper bounds on the rank of each alternative in order to narrow down the set of categories that each alternative can be assigned to. We demonstrate our approach on two applications from practice