Morphing Ensemble Kalman Filters

A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF) with the ideas of morphing and registration from image processing. This results in filters suitable for nonlinear problems whose solutions exhibit moving coherent features, such as thin interfaces in wildfire modeling. The ensemble members are represented as the composition of one common state with a spatial transformation, called registration mapping, plus a residual. A fully automatic registration method is used that requires only gridded data, so the features in the model state do not need to be identified by the user. The morphing EnKF operates on a transformed state consisting of the registration mapping and the residual. Essentially, the morphing EnKF uses intermediate states obtained by morphing instead of linear combinations of the states.Comment: 17 pages, 7 figures. Added DDDAS references to the introductio

An information theoretic characterisation of auditory encoding.

The entropy metric derived from information theory provides a means to quantify the amount of information transmitted in acoustic streams like speech or music. By systematically varying the entropy of pitch sequences, we sought brain areas where neural activity and energetic demands increase as a function of entropy. Such a relationship is predicted to occur in an efficient encoding mechanism that uses less computational resource when less information is present in the signal: we specifically tested the hypothesis that such a relationship is present in the planum temporale (PT). In two convergent functional MRI studies, we demonstrated this relationship in PT for encoding, while furthermore showing that a distributed fronto-parietal network for retrieval of acoustic information is independent of entropy. The results establish PT as an efficient neural engine that demands less computational resource to encode redundant signals than those with high information content

Separating a Real-Life Nonlinear Image Mixture

When acquiring an image of a paper document, the image printed on the back page sometimes shows through. The mixture of the front- and back-page images thus obtained is markedly nonlinear, and thus constitutes a good real-life test case for nonlinear blind source separation. This paper addresses a difficult version of this problem, corresponding to the use of "onion skin" paper, which results in a relatively strong nonlinearity of the mixture, which becomes close to singular in the lighter regions of the images. The separation is achieved through the MISEP technique, which is an extension of the well known INFOMAX method. The separation results are assessed with objective quality measures. They show an improvement over the results obtained with linear separation, but have room for further improvement

Analysis of surface folding patterns of diccols using the GPU-Optimized geodesic field estimate

Localization of cortical regions of interests (ROIs) in the human brain via analysis of Diffusion Tensor Imaging (DTI) data plays a pivotal role in basic and clinical neuroscience. In recent studies, 358 common cortical landmarks in the human brain, termed as Dense Indi- vidualized and Common Connectivity-based Cortical Landmarks (DICCCOLs), have been identified. Each of these DICCCOL sites has been observed to possess fiber connection patterns that are consistent across individuals and populations and can be regarded as predictive of brain function. However, the regularity and variability of the cortical surface fold patterns at these DICCCOL sites have, thus far, not been investigated. This paper presents a novel approach, based on intrinsic surface geometry, for quantitative analysis of the regularity and variability of the cortical surface folding patterns with respect to the structural neural connectivity of the human brain. In particular, the Geodesic Field Estimate (GFE) is used to infer the relationship between the structural and connectional DTI features and the complex surface geometry of the human brain. A parallel algorithm, well suited for implementation on Graphics Processing Units (GPUs), is also proposed for efficient computation of the shortest geodesic paths between all cortical surface point pairs. Based on experimental results, a mathematical model for the morphological variability and regularity of the cortical folding patterns in the vicinity of the DICCCOL sites is proposed. It is envisioned that this model could be potentially applied in several human brain image registration and brain mapping applications

A real-time networked camera system:a scheduled distributed camera system reduces the latency

This report presents the results of a Real-time Networked Camera System, com-missioned by the SAN Group in TU/e. Distributed Systems are motivated by two reasons, the first reason is the physical environment as a requirement and the second reason is to provide a better Quality of Service (QoS). This project describes the distributed system with a video processing application. The aim is to deal with the distributed system as one system thus minimizing delays while keeping the predictability in a real-time context. Time is the most crucial ingredient for the real-time systems in the sense that the tasks within the application should meet with the task deadline. With respect to the distributed system we need to consider a couple of issues. The first one is to have a distributed system and a modular application that is mapped to multiple system nodes. The second issue is to schedule the modules collectively and the third is to propose a solution when shared resource(s) (such as the network) are required by several nodes at the same time. In order to provide a distributed system, we connect 2 cameras with 1 PC via a network switch. Video processing has two parts; the first part consists of creating a frame, encoding the frame, and streaming it to the network and the second part deals with receiving the frame, decoding the frame, and displaying the frame. The first part is running on the cameras and the second part is running on the PC. In order to give real-time behavior to the system, the system components should provide the real-time behavior. The camera is installed with the µC/OS-II (Open Source Real-time Kernel). We investigated the Real-time Operating System and its installation on the PC. In order to provide resource management to the shared resources, we designed and implemented Admission control which controls access to the required con-nection to the PC. We designed and implemented a component to delay the start of any of the cameras in order to synchronize the network utilization. We also designed an enforcement component to allow the tasks to run as much as they should and monitor the frames streamed to the network. The results show that with the Admission Control, cameras only send as many frames as the network can transport. The given start delay to the system shows that overlap can be prevented, but we could not evaluate it because of the semi-tested/unreleased code which is provided by the camera providers. The source code we used is the test source code which was not mature