Hierarchical isometry properties of hierarchical measurements

Compressed sensing studies linear recovery problems under structure assumptions. We introduce a new class of measurement operators, coined hierarchical measurement operators, and prove results guaranteeing the efficient, stable and robust recovery of hierarchically structured signals from such measurements. We derive bounds on their hierarchical restricted isometry properties based on the restricted isometry constants of their constituent matrices, generalizing and extending prior work on Kronecker-product measurements. As an exemplary application, we apply the theory to two communication scenarios. The fast and scalable HiHTP algorithm is shown to be suitable for solving these types of problems and its performance is evaluated numerically in terms of sparse signal recovery and block detection capability

Stability analysis of digital microwave power amplifiers

This work presents a stability analysis of microwave power amplifiers (PAs) driven by binary pulse trains, as in the case of class-S PAs. First, using a simplified digital PA test bench in class-D configuration, different qualitative behaviors are obtained when varying the pulsewidth, including subharmonic and incommensurable oscillations. The mechanisms affecting the stability properties are studied with a harmonic balance-based formulation, by means of pole-zero identification and bifurcation detection. A sufficiently high number of harmonic components must be considered, together with the Krylov decomposition for an efficient computation of the inverse of the Jacobian matrix. It is demonstrated that, when varying the pulsewidth, the distinct pairs of complex-conjugate poles may shift to the right-hand side of the complex plane and, therefore, lead to different kinds of unstable behavior. This phenomenon is related to the dependence of the critical poles on the average value of the input signal. Boundaries of the various types of unstable behavior are traced in the plane defined by the pulse repetition rate and pulsewidth, using bifurcation detection techniques. All the predicted phenomena have been confirmed experimentally. In a second step, the algorithms derived from the simple class-D circuit are transferred to study the stability of a more complex tri-band class-S amplifier. It has been analyzed versus the input bitrate, obtaining a fully stable behavior that has been validated experimentally.This work has been supported by the Spanish Government under contract TEC2014-60283-C3-1-R, the European Regional Development Fund (ERDF/FEDER) and the Parliament of Cantabria (12.JP02.64069)

Towards realistic artificial benchmark for community detection algorithms evaluation

Assessing the partitioning performance of community detection algorithms is one of the most important issues in complex network analysis. Artificially generated networks are often used as benchmarks for this purpose. However, previous studies showed their level of realism have a significant effect on the algorithms performance. In this study, we adopt a thorough experimental approach to tackle this problem and investigate this effect. To assess the level of realism, we use consensual network topological properties. Based on the LFR method, the most realistic generative method to date, we propose two alternative random models to replace the Configuration Model originally used in this algorithm, in order to increase its realism. Experimental results show both modifications allow generating collections of community-structured artificial networks whose topological properties are closer to those encountered in real-world networks. Moreover, the results obtained with eleven popular community identification algorithms on these benchmarks show their performance decrease on more realistic networks

A metaobject architecture for fault-tolerant distributed systems : the FRIENDS approach

The FRIENDS system developed at LAAS-CNRS is a metalevel architecture providing libraries of metaobjects for fault tolerance, secure communication, and group-based distributed applications. The use of metaobjects provides a nice separation of concerns between mechanisms and applications. Metaobjects can be used transparently by applications and can be composed according to the needs of a given application, a given architecture, and its underlying properties. In FRIENDS, metaobjects are used recursively to add new properties to applications. They are designed using an object oriented design method and implemented on top of basic system services. This paper describes the FRIENDS software-based architecture, the object-oriented development of metaobjects, the experiments that we have done, and summarizes the advantages and drawbacks of a metaobject approach for building fault-tolerant system

FRIENDS - A flexible architecture for implementing fault tolerant and secure distributed applications

FRIENDS is a software-based architecture for implementing fault-tolerant and, to some extent, secure applications. This architecture is composed of sub-systems and libraries of metaobjects. Transparency and separation of concerns is provided not only to the application programmer but also to the programmers implementing metaobjects for fault tolerance, secure communication and distribution. Common services required for implementing metaobjects are provided by the sub-systems. Metaobjects are implemented using object-oriented techniques and can be reused and customised according to the application needs, the operational environment and its related fault assumptions. Flexibility is increased by a recursive use of metaobjects. Examples and experiments are also described

Using consistent subcuts for detecting stable properties

We present a general protocol for detecting whether a property holds in a distributed system, where the property is a member of a subclass of stable properties we call the locally stable properties. Our protocol is based on a decentralized method for constructing a maximal subset of the local states that are mutually consistent, which in turn is based on a weakened version of vectored time stamps. The structure of our protocol lends itself to refinement, and we demonstrate its utility by deriving some specialized property-detection protocols, including two previously known protocols that are known to be effective

Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instance-aware semantic segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-level features during the feature extracting as text instance may rely on finer feature expression compared to general objects. It detects and segments the text instance jointly and simultaneously, leveraging merits from both semantic segmentation task and region proposal based object detection task. Not involving any extra pipelines, our approach surpasses the current state of the art on multi-oriented scene text detection benchmarks: ICDAR2015 Incidental Scene Text and MSRA-TD500 reaching Hmean 84.1% and 82.0% respectively. Morever, we report a baseline on total-text containing curved text which suggests effectiveness of the proposed approach.Comment: Accepted by ICPR201