Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node's measurement and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighboring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly encoding multiple sources. We focus on the case where node measurements are in form of noisy linearly mixed combinations of the sources and the acoustic channel mixing matrices are invertible. For this problem, we derive the rate-distortion function for vector Gaussian sources and under covariance distortion constraints.Comment: 10 pages, to be presented at the IEEE DCC'1

Distributed Remote Vector Gaussian Source Coding with Covariance Distortion Constraints

In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the optimal rate for encoding the observations subject to a covariance matrix distortion constraint and in the presence of side information at the decoder. For this problem, we derive lower and upper bounds on the rate-distortion function (RDF) for the Gaussian case, which in general do not coincide. We then provide some cases, where the RDF can be derived exactly. We also show that previous results on specific instances of this problem can be generalized using our results. We finally show that if the distortion measure is the mean squared error, or if it is replaced by a certain mutual information constraint, the optimal rate can be derived from our main result.Comment: This is the final version accepted at ISIT'1

Source Coding in Networks with Covariance Distortion Constraints

We consider a source coding problem with a network scenario in mind, and formulate it as a remote vector Gaussian Wyner-Ziv problem under covariance matrix distortions. We define a notion of minimum for two positive-definite matrices based on which we derive an explicit formula for the rate-distortion function (RDF). We then study the special cases and applications of this result. We show that two well-studied source coding problems, i.e. remote vector Gaussian Wyner-Ziv problems with mean-squared error and mutual information constraints are in fact special cases of our results. Finally, we apply our results to a joint source coding and denoising problem. We consider a network with a centralized topology and a given weighted sum-rate constraint, where the received signals at the center are to be fused to maximize the output SNR while enforcing no linear distortion. We show that one can design the distortion matrices at the nodes in order to maximize the output SNR at the fusion center. We thereby bridge between denoising and source coding within this setup

Analysis of cost effectiveness of screening Danish men aged 65 for abdominal aortic aneurysm

Objective To assess the cost effectiveness of screening men aged 65 for abdominal aortic aneurysm

Regional Longitudinal Myocardial Deformation Provides Incremental Prognostic Information in Patients with ST-Segment Elevation Myocardial Infarction

Global longitudinal systolic strain (GLS) has recently been demonstrated to be a superior prognosticator to conventional echocardiographic measures in patients after myocardial infarction (MI). The aim of this study was to evaluate the prognostic value of regional longitudinal myocardial deformation in comparison to GLS, conventional echocardiography and clinical information.In total 391 patients were admitted with ST-Segment elevation myocardial infarction (STEMI), treated with primary percutaneous coronary intervention and subsequently examined by echocardiography. All patients were examined by tissue Doppler imaging (TDI) and two-dimensional strain echocardiography (2DSE).During a median-follow-up of 5.3 (IQR 2.5-6.1) years the primary endpoint (death, heart failure or a new MI) was reached by 145 (38.9%) patients. After adjustment for significant confounders (including conventional echocardiographic parameters) and culprit lesion, reduced longitudinal performance in the anterior septal and inferior myocardial regions (but not GLS) remained independent predictors of the combined outcome. Furthermore, inferior myocardial longitudinal deformation provided incremental prognostic information to clinical and conventional echocardiographic information (Harrell's c-statistics: 0.63 vs. 0.67, p = 0.032). In addition, impaired longitudinal deformation outside the culprit lesion perfusion region was significantly associated with an adverse outcome (p<0.05 for all deformation parameters).Regional longitudinal myocardial deformation measures, regardless if determined by TDI or 2DSE, are superior prognosticators to GLS. In addition, impaired longitudinal deformation in the inferior myocardial segment provides prognostic information over and above clinical and conventional echocardiographic risk factors. Furthermore, impaired longitudinal deformation outside the culprit lesion perfusion region seems to be a paramount marker of adverse outcome