École Polytechnique Fédérale de Lausanne
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Intraarticular application of superparamagnetic nanoparticles and their uptake by synovial membrane—an experimental study in sheep
No full textA superparamagnetic iron oxide nanoparticle, coated with polyvinyl alcohol, (PVA-SPION) and its fluorescently functionalized analogue (amino-PVA-Cy3.5-SPION) were compared in vivo as proof of principle for future use in magnetic drug targeting in inflammatory joint diseases. They were injected either intraarticularly or periarticularly and their uptake by cells of the synovial membrane was evaluated. Uptake was completed in 48 h and was enforced by an extracorporally applied magnet.LT
Lossy Network Correlated Data Gathering with High-Resolution Coding
No full textSensor networks measuring correlated data are considered, where the task is to gather data from the network nodes to a sink. A specific scenario is addressed, where data at nodes are lossy coded with high-resolution, and the information measured by the nodes has to be reconstructed at the sink within both certain total and individual distortion bounds. The first problem considered is to find the optimal transmission structure and the rate-distortion allocations at the various spatially located nodes, such as to minimize the total power consumption cost of the network, by assuming fixed nodes positions. The optimal transmission structure is the shortest path tree and the problems of rate and distortion allocation separate in the high-resolution case, namely, first the distortion allocation is found as a function of the transmission structure, and second, for a given distortion allocation, the rate allocation is computed. The second problem addressed is the case when the node positions can be chosen, by finding the optimal node placement for two different targets of interest, namely total power minimization and network lifetime maximization. Finally, a node placement solution that provides a tradeoff between the two metrics is proposed.LCA
The Contourlet Transform: An Efficient Directional Multiresolution Image Representation
No full textThe limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. The main challenge in exploring geometry in images comes from the discrete nature of the data. Thus, unlike other approaches, such as curvelets, that first develop a transform in the continuous domain and then discretize for sampled data, our approach starts with a discrete-domain construction and then studies its convergence to an expansion in the continuous domain. Specifically, we construct a discrete-domain multiresolution and multidirection expansion using nonseparable filter banks, in much the same way that wavelets were derived from filter banks. This construction results in a flexible multiresolution, local, and directional image expansion using contour segments, and, thus, it is named the contourlet transform. The discrete contourlet transform has a fast iterated filter bank algorithm that requires an order N operations for N-pixel images. Furthermore, we establish a precise link between the developed filter bank and the associated continuous-domain contourlet expansion via a directional multiresolution analysis framework. We show that with parabolic scaling and sufficient directional vanishing moments, contourlets achieve the optimal approximation rate for piecewise smooth functions with discontinuities along twice continuously differentiable curves. Finally, we show some numerical experiments demonstrating the potential of contourlets in several image processing applications.LCA
Power spectra of random spike fields and related processes
Get PDFThis article reviews known results and contains new ones concerning the power spectra of large classes of signals and random fields driven by an underlying point process, such as spatial shot noises (with random impulse response and arbitrary basic stationary point processes described by their Bartlett spectrum), and signals or fields sampled at random times or points (where again the sampling point process is quite general). We also obtain the Bartlett spectrum for the general linear Hawkes spatial branching point process (with random fertility rate and general immigrant process described by its Bartlett spectrum). We then obtain the Bochner spectrum of general spatial linear birth and death processes. Finally we adress the issue of random sampling, and of the linear reconstruction of a signal from its random samples, reviewing and extending former results.LCA
Ultrawide Bandwidth Signals as Shot-Noise: a Unifying Approach
No full textWe present a shot noise based model for a large family of ultrawide bandwidth (UWB) signals. These include time-hopping and direct-sequence signaling with pulse position, interval, and amplitude modulations. Each specific signal is constructed by adding features to a basic model in a modular, simple, and tractable way. Our work unifies the contributions scattered in the literature and provides a general approach that allows various extensions of previous works as well as new results. The exact power spectrum is then evaluated using shot noise spectral theory, which provides a simpler, systematic, and rigorous approach to the spectra evaluation of complicated UWB signals. The strength of our methodology is that different features of the signal model contribute clearly and separately to the resulting spectral expressions.LCA
High Order Balanced MultiWavelets: Theory, Factorization and Design
No full textThis paper deals with multiwavelets and the different properties of approximation and smoothness that are associated with them. In particular, we focus on the important issue of the preservation of discrete time polynomial signals by multiwavelet based filter banks. We give here a precise definition of balancing for higher degree discrete time polynomial signals and link it to a very natural factorization of the lowpass refinement mask that is the counterpart of the well-known 'zeros at pi' condition on the scaling function in the usual wavelet framework. This property of balancing proves then to be central to the issues of the preservation of smooth signals by the filter bank, the approximation power of the multiresolution analysis and the smoothness of the scaling functions and wavelets. Using these new results, we are able to construct a family of orthogonal multiwavelets with symmetries and compact support that is indexed by the order of balancing. We also give the minimum length orthogonal multiwavelets for any balancing order.LCA
A self-organizing access structure for P2P information systems
No full textPeer-To-Peer systems are driving a major paradigm shift in the era of genuinely distributed computing. Gnutella is a good example of a Peer-To-Peer success story: a rather simple software enables Internet users to freely exchange files, such as MP3 music files. But it shows up also some of the limitations of current P2P information systems with respect to their ability to manage data efficiently. In this paper we introduce P-Grid, a scalable access structure that is specifically designed for Peer-To-Peer information systems. P-Grids are constructed and maintained by using randomized algorithms strictly based on local interactions, provide reliable data access even with unreliable peers, and scale gracefully both in storage and communication cost. Keywords: Peer-To-Peer computing, Distributed Indexing, Distributed Databases, Randomized Algorithms.LSI
To Code, Or Not To Code: On the Optimality of Symbol-by-Symbol Communication
No full textWhen is uncoded transmission optimal? This paper derives easy-to-check necessary and sufficient conditions that do not require finding the rate-distortion and the capacity-cost functions. We consider the symbol-by-symbol communication of discrete-time memoryless sources across discrete-time memoryless channels, using single-letter coding and decoding. This is an optimal communication system if and only if the channel input cost function and the distortion measure can be written in a form that we explicitly characterize. There are two well-known examples where uncoded transmission is optimal. The first example consists of a Gaussian source and a Gaussian channel. In the second example the source and the channel are binary. But these are just two out of infinitely many examples that one can construct in a straightforward way from our results. As a matter of fact, one can arbitrarily pick the source distribution, the single-letter encoder/decoder, and the channel conditional distribution, and make the system optimal by choosing the channel input cost function and the distortion measure according to the given closed-form expression. The paper also discusses the advantages of uncoded transmission for non-ergodic channels and multiuser communications. Finally, some results concerning -block-length codes are obtained.LCAVLIN
Digital DS-CDMA receiver working below the chip rate: theory and design
Get PDFWe consider the problem of designing low-complexity digital receivers for CDMA systems operating over channels with single or multiple propagation paths. We specifically exploit a finite rate of innovation property of CDMA signals and develop a method that leads to an efficient solution of the combined problem of multipath channel estimation and signal detection from a low-dimensional subspace of a received signal. Unlike existing schemes that typically resort to chip rate sampling and manipulate with large correlation matrices, our framework allows for digital CDMA receivers to operate at a significantly lower sampling rate, chosen to be close to a rate of innovation of a received signal. Our approach, therefore, can considerably reduce computational requirements compared to existing solutions while providing similar performances, and allows to use slower A/D converters, thus reducing power consumption.LCA