Attenuation of ultrasonic waves is often assumed linear with respect to frequency in biological applications whereas it is considered quadratic when the propagation occurs in the atmosphere or the water. In the latter case, other studies show that a Gaussian propagation duration can explain this attenuation behavior and provide a model for the energy loss in the stationary limit. The present paper defines an equivalent random propagation duration with Cauchy distribution, which is appropriate for the propagation of ultrasound through tissue. The model adds an unobserved noise that represents the signal deterioration. In addition, the model agrees with the mode downshift in the case of a narrowband signal.

The present paper decomposes the study of wake vortex's scattering characteristics into three key problems. Based on the study of these three problems in detail, we obtained the scattering characteristics of the wake vortex, which include the frequency characteristic of RCS, the radiation pattern, the relation between RCS and the detection range, and the time evolution characteristic of RCS. Research findings can provide supports for the development of radar detection technology on wake vortex.

Considering the emergence of telemedicine applications, different links such as fixed access network (PSTN), mobile access network (GSM/GPRS and future UMTS) or satellite interfacing (DVB-RCS technology) are involved in e-health applications. These are liable to induce errors and/or missing packets on the received data. Therefore the recovering of missing samples for biomedical signals is of great interest. This paper proposes a reconstruction method for ECG signals which is a combination of a left-sided and right-sided autoregressive (AR) model, and the well-known Gerchberg-Papoulis (GP) method. The proposed interpolation algorithm takes into account the samples before and after the missing ones to estimate a forward and a backward AR model. These estimates are used as an initialization of the original GP method. Results show that this interpolation method represents a really suitable technique to ECG reconstruction in a possible corrupted transmission.

Routers-assisted congestion control protocols, also known as Explicit Rate Notification (ERN) protocols, implement complex algorithms inside a router in order to provide both high link utilization and high fairness. Thus, routers assisted approaches overcome most of the end-to-end protocols problems in large bandwidth-delay product networks. Today, routers-assisted protocols cannot be deployed in heterogeneous networks (e.g., Internet) due to their non-compliance with current network protocols. Nevertheless, these approaches can be deployed in satellite networks in the context of splitting PEPs. In this work, as routers-assisted protocols can use TCP algorithms to enable reliability, we aim at understanding and providing a detailed view of the impact of such algorithms on the performance obtained by routers-assisted protocols over satellite links. In particular, we both study XCP and P-XCP proposals over long delay, lossy and asymmetric links and propose a ns-2 implementation of the P-XCP protocol to the satellite community. To the best of our knowledge, this study is the first one which tackles the impact of TCP internal mechanisms on top of XCP protocol. Our main conclusion is that TCP New Reno Slow But Steady variant on top of P-XCP is to date, the most optimal configuration for satellite proxies.

Packet loss due to misrouted or delayed packets in voice over IP leads to huge voice quality degradation. This paper presents a packet loss concealement algorithm which is inde pendant from the vocoder. This method relies on hidden Marko v model (HMM). A new voicing parameter is introduced to get ove r voiced/unvoiced sound separation and use a unique HMM. Since best parameter for prediction are not necessarily the best ones for synthesis, we introduce two separate vectors: the first one dedicated to the analysis of the signal and the second one featured for the synthesis of missing part. Performances of the proposed system are evaluated on parts of well-known speech corpora, leading to promising results.

This paper studies a new unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of endmembers which are supposed to be random in order to model uncertainties regarding their knowledge. More precisely, endmembers are modeled as Gaussian vectors with known means (resulting from an endmember extraction algorithm such as the famous N-FINDR or VCA algorithm). This paper proposes to estimate the mixture coefficients (referred to as abundances) using a Bayesian algorithm. Suitable priors are assigned to the abundances in order to satisfy positivity and additivity constraints whereas a conjugate prior is chosen for the variance. The computational complexity of the resulting Bayesian estimators is alleviated by constructing an hybrid Gibbs algorithm to generate abundance and variance samples distributed according to the posterior distribution of the unknown parameters. The associated hyperparameter is also generated. The performance of the proposed methodology is evaluated thanks to simulation results conducted on synthetic and real images.

Packet loss due to misrouted or delayed packets in voice over IP leads to huge voice quality degradation. Packet loss con- cealment algorithms try to enhance the quality of the speech. This paper presents a new packet loss concealment algorithm which relies on one hidden Markov model. For this purpose, we introduce a continuous observation vector well-suited for silence, voiced and unvoiced sounds. We show that having a global HMM is relevant for this application. The proposed system is evaluated using standard PESQ score in a real- world application.

SpaceWire is a standard for on-board satellite networks chosen by the ESA as the basis for future data-handling architectures. However, network designers need tools to ensure that the network is able to deliver critical messages on time. Current research only seek to determine probabilistic results for end-to-end delays on wormhole networks like SpaceWire. This does not provide sufficient guarantee for critical traffic. Thus, in this paper, we propose a method to compute an upper-bound on the worst-case end-to-end delay of a packet in a SpaceWire network.

In automatic speech analysis, voicing articulatory is often defined as a binary decision: voiced or unvoiced. Lin- guists agree that this articulatory should be continuous. In this paper, we present a new approach to compute a con- tinuous voicing indicator of a speech frame. This voic- ing percentage is then evaluated in both a segmentation process and a speech recognition task. Promising results show that this continuous voicing percentage may be used as a reliable voicing indicator.

Detecting the presence of non-stationarity events in a signal is a challenge that is still not taken up. The aim of this paper is to make a contribution to this key issue. We already proposed a non-stationarity detection defined in time-frequency domain in order to control the invariance of the time-frequency statistics. In this paper, in order to be not limited by the time and frequency resolution of a time-frequency approach, we propose another test in frequency domain. In frequency domain, the problem can be cast by taking advantage of the normalized-variance properties of a spectral estimator when analyzing non-stationary signals. This second test will confirm, invalidate or detect new frequency localizations of non-stationarities. Finally, the main contribution of the paper is to propose a stationary index defined so as to merge the information given by these two tests and to allow an alarm to be raised for a high level of non-stationarities. Applications on real-world signals show the pertinence of this new index.