Comparison of the long range polymer chain dynamics of polystyrene and cis-polyisoprene using polymers randomly labeled with pyrene

The ability of the Fluorescence Blob Model (FBM) to probe the chain dynamics of a polymer backbone was verified for the first time by investigating whether it responds to known differences in backbone flexibility for flexible cis-polyisoprene (PIP) and more sterically hindered polystyrene (PS), both randomly labeled with pyrene. For comparable pyrene contents, the steady-state fluorescence spectra indicated that Py-PIP formed considerably more excimer than the Py-PS samples. Analysis of the fluorescence decays with the FBM provided the rate constant for intramolecular excimer formation. This rate constant was much larger for Py-PIP than for Py-PS, in agreement with the enhanced excimer formation observed for Py-PIP. The enhanced ability of Py-PIP to form excimer is attributed to the PIP backbone being less sterically hindered than the PS backbone. This study is the first example of a comparison of the long range polymer chain dynamics for two different polymeric backbones randomly labeled with pyrene.     

Congruent unilateral impairments for real and imagined hand movements

The chronometry of imagined and actual movements was investigated in a patient with a unilateral lesion of the motor cortex. Motor imagery generated highly accurate estimates of motor performance in a variety of situations, reflecting the hypokinesia of the contralesional hand. There were parallel increases in mental and actual movement times from proximal to distal limb segments. Bimanual movements adopted the slower speed of the impaired hand in both conditions. Imagined motor sequences to the beat of a metronome predicted the maximum speed reached in actual performance. Finally, visually guided pointing showed the same target-size effects in the imagery and movement conditions. The results are in agreement with the hypothesis that common cerebral motor representations are activated when imaging and planning voluntary movements.     

Perfect reconstruction versus MMSE filter banks in source coding

Classically, the filter banks (FBs) used in source coding schemes have been chosen to possess the perfect reconstruction (PR) property or to be maximally selective quadrature mirror filters (QMFs). This paper puts this choice back into question and solves the problem of minimizing the reconstruction distortion, which, in the most general case, is the sum of two terms: a first one due to the non-PR property of the FB and the other being due to signal quantization in the subbands. The resulting filter banks are called minimum mean square error (MMSE) filter banks. Several quantization noise models are considered. First, under the classical white noise assumption, the optimal positive bit rate allocation in any filter bank (possibly nonorthogonal) is expressed analytically, and an efficient optimization method of the MMSE filter banks is derived. Then, it is shown that while in a PR FB, the improvement brought by an accurate noise model over the classical white noise one is noticeable, it is not the case for the MMSE FB. The optimization of the synthesis filters is also performed for two measures of the bit rate: the classical one, which is defined for uniform scalar quantization, and the order-one entropy measure. Finally, the comparison of rate-distortion curves (where the distortion is minimized for a given bit rate budget) enables us to quantify the SNR improvement brought by MMSE solutions     

On-line blind multichannel equalization based on mutually referenced filters

This paper presents a novel approach to the blind linear equalization of possibly nonminimum phase and time-varying communication channels. In the context of channel diversity, we introduce the concept of mutually referenced equalizers (MREs) in which several filters are considered, the outputs of which act as training signals for each other. A corresponding (constrained) multidimensional mean-square error (MSE) cost function is derived, the minimization of which is shown to be a necessary and sufficient condition for equalization. The links with a standard linear prediction problem are demonstrated. The proposed technique exhibits properties of important practical concern: 1) the proposed algorithm is globally convergent. 2) Simple closed-form solutions exist for the MREs, but the MREs also lend themselves readily to adaptive implementation. In particular, the recursive least-squares (RLS) algorithm can be used to offer optimal convergence rate. 3) The MRE method provides a solution for all equalization delays, which results in robustness properties with respect to SNR and ill-defined channel lengths.     

Variable neighborhood descent with iterated local search for routing and wavelength assignment

In this work we treat the Routing and Wavelength Assignment (RWA) with focus on minimizing the number of wavelengths to route demand requests. Lightpaths are used to carry the traffic optically between origin-destination pairs. The RWA is subjected to wavelength continuity constraints, and a particular wavelength cannot be assigned to two different lightpaths sharing a common physical link. We develop a Variable Neighborhood Descent (VND) with Iterated Local Search (ILS) for the problem. In a VND phase we try to rearrange requests between subgraphs associated to subsets of a partition of the set of lightpath requests. In a feasible solution, lightpaths belonging to a subset can be routed with the same wavelength. Thus, the purpose is to eliminate one subset of the partition. When VND fails, we perform a ILS phase to disturb the requests distribution among the subsets of the partition. An iteration of the algorithm alternates between a VND phase and a ILS phase. We report computational experiments that show VND-ILS was able to improve results upon powerful methods proposed in the literature.     

Oversampled filter banks as error correcting codes: theory and impulse noise correction

Oversampled filter banks (OFBs) provide an overcomplete representation of their input signal. This paper describes how OFBs can be considered as error-correcting codes acting on real or complex sequences, very much like classical binary convolutional codes act on binary sequences. The structured redundancy introduced by OFBs in subband signals can be used to increase robustness to noise. In this paper, we define the notions of code subspace, syndrome, and parity-check polynomial matrix for OFBs. Furthermore, we derive generic expressions for projection-based decoding, suitable for the case when a simple second-order model completely characterizes the noise incurred by subband signals. We also develop a nonlinear hypotheses-test based decoding algorithm for the case when the noise in subbands is constituted by a Gaussian background noise and impulsive errors (a model that adequately describes the action of both quantization noise and transmission errors). Simulation results show that the algorithm effectively removes the effect of impulsive errors occurring with a probability of 10/sup -3/.     

émergence de la distinction personne-objet.

Investigated the emergence of the cognitive ability to distinguish persons and objects during the first few months of life. Thirty-eight infants took part in 2 experimental sessions, the first conducted at the age of 4 wks, the second at 10 wks. Each session consisted of 6 episodes in which the infant's mother, a stranger and a doll were presented under 2 conditions: "active" or "inactive." Infants' facial expressions, visual fixations and vocalizations were analyzed. Several differences were observed in infants behaviours towards the persons and the doll: the babies smiled more at their mother and at the stranger and vocalized more to people than to the doll. However, these differences were closely related to the activity of the stimuli presented. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A parametric blind subspace identification: robustness issue

Subspace techniques became in recent years a popular tool for blind identification of single-input multiple output finite-impulse response (SIMO-FIR) systems. However, a serious drawback of these methods is high sensitivity to the order modeling errors. In this contribution, we show that a parametric approach of subspace methods, i.e., exploiting the specular structure of the propagation channel, is intrinsically robust to channel order overestimation     

On the use of cascade structure to correct impulsive noise in multicarrier systems

We propose a new decoding algorithm based on a cascade structure for impulsive noise correction in multicarrier systems such as Orthogonal Frequency Division Multiplexing (OFDM) based systems. This new cascade structure based algorithm has the advantage to lead on one hand to a reducedcomplexity implementation in an OFDM demodulator and on the other hand to overcome the lacks of other algorithms dedicated for impulsive noise correction. To do so, we start the derivation by investigating closed-form analytical expressions of the a priori probabilities used in hypotheses tests that are necessary for the different steps needed for the execution of the cascade structure based decoding algorithm. Such closed-form expressions for the a priori probabilities, result in efficient setups of the threshold values used for the execution of the decoding algorithm. Furthermore, we show that this cascade structure can be applied to efficiently cancel the impulsive noise in OFDM systems. As the clipping event, present in OFDM systems, can be seen as an additive impulsive noise, we prove that after introducing some minor modifications, we can apply the proposed cascade structure to significantly reduce the Peak to Average Power Ratio (PAPR) level in such systems. Simulation results are given to illustrate the usefulness of the proposed algorithm results in practical OFDM based communication systems such as Hiperlan 2.