Nonlinearity-robust linear acoustic echo canceller using the maximum Correntropy criterion

For the problem of acoustic echo cancellation (AEC) with nonlinear distortions, we propose to use a linear adaptive filter that maximizes the Correntropy similarity measure instead of the conventional minimization of the mean squared error (MSE) criterion. The maximum Correntropy criterion (MCC) offers robustness to outliers and impulsive noise, which is interesting for the case of speech signal coupled with nonlinearities. To assess the performance of the algorithm, we consider a hard-clipping memoryless saturation nonlinearity. Our simulation results show very interesting performance of the normalized MCC-based linear adaptive filter for the echo return loss enhancement (ERLE) and misalignment measures compared to the MSE-based normalized least mean squares (NLMS) approach. Furthermore, the NMCC adaptive filter has a similar computational complexity as the NLMS algorithm, which makes it very attractive in practical implementations

Electrodynamic loudspeaker linearization using a low complexity pth-Order inverse nonlinear filter

Nonlinear distortions are very challenging to tackle in electromechanical loudspeakers. They are observed in large signals mode, where high amplitude stimulus drives different components of the transducer to operate in their nonlinear region, resulting in harmonic and intermodulation distortions in the reproduced sounds. Many linearization schemes have been proposed to address this problem, they operate by pre-distorting the input signal before exciting the loudspeaker, in the aim of radiating distortion-free sound waves. In this work, we are interested in the performance evaluation of a low computational complexity feedforward linearization structure which is based on the pth order inverse of a one-dimension Volterra model of the driver. The scheme is designed to compensate for the 2nd and 3rd harmonic distortions. We will study the effect of varying the input voltage amplitude on the harmonic distortions reduction performance. A lumped-parameters model with parameters of a real driver will be used for the evaluation

A community‐based social P2P network for sharing human life digital memories

Social peer‐to‐peer (P2P) networks are usually designed by reflecting a user's interest/behavior for structuring the underlying network. Human interest is affected by various factors such as age, locality, and so on which changes after some time. The behavior when reflected in a network, results in peers moving within the network in order to connect the peer with peers of the same behavior/interest. Especially in community‐based schemes when a peer leaves a community the data that a peer was sharing will not be accessible in the same community anymore. It has an effect on the performance of the network due to the inaccessibility of data and the unavailability of connections, which affect network robustness. We address this issue by considering entities in data in the form of digital memories of a user and structuring network according to entity‐based communities. The simulation results for the proposed entity‐based community are demonstrated, which shows the effect on network performance during varying network size and traffic

Projection des relations SNOMED CT entre les termes de deux terminologies (CIM10 et SNOMED 3.5)

National audienc

Tactical Waypoint Maps: Towards Imitating Tactics in FPS Games

Thurau C, Bauckhage C. Tactical Waypoint Maps: Towards Imitating Tactics in FPS Games. In: Merabti M, Lee N, Overmars MH, eds. Proc. 3rd International Game Design and Technology Workshop and Conference (GDTW’05 ). ACM; 2005: 140-144.Modern FPS games do not only demand fast reactions from the participating human players but also require them to think tactically and strategically. While artifical players usually surpass their human counterparts in reaction time and accuracy, they are hopelessly lost if it comes to tactical and strategical gameplay. In this paper, we propose Bayesian imitation learning in conjunction with tactical waypoint maps as a means to learn tactical behaviors suited for "1 vs. 1" game situations. The empirical basis for our approach is given by the data contained in recordings of matches between human players. Experimental results underline the usability of tactical waypointmaps and bayesian imitation learning for the acquisition and generation of new behaviors in artificial players

TiO2 waveguides thin films prepared by sol-gel method on glass substrates with and without ZnO underlayer

TiO2 thin films have been deposited on glass substrates with and without ZnO underlayer by sol-gel dip coating process. XRD patterns show the formation of anatase phase with the diffraction lines (1 0 1) and (2 0 0) in TiO2/glass sample. In TiO2/(ZnO/glass) sample, TiO2 is composed of anatase phase with the diffraction line (2 0 0) but the diffraction peaks of ZnO wurtzite are also well-defined. The determination of the refractive index and the thickness of the waveguiding layers has been performed by m-lines spectroscopy. The thickness of TiO2 thin films deduced by Rutheford Backscattering Geometry (RBS) agrees well with that obtained by m-lines spectroscopy. TiO2/glass sample exhibits one guided TE0 and TM0 polarized modes. In TiO2/(ZnO/glass) sample, only, TE0 single mode has been excited due to cutoff condition