2,964 research outputs found

    Blind extraction using fractional lower-order statistics

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    In traditional method to blindly extract interesting source signals sequentially, the second-order or higher-order statistics of signals are often utilized. However, for impulsive sources, both of the second-order and higher-order statistics may degenerate. Therefore, it is necessary to exploit new method for the blind extraction of impulsive sources. Based on the best compression-reconstruction principle, a novel model is proposed in this work, together with the corresponding algorithm. The proposed method can be used for blind extraction of sources which are distributed from alpha stable process. Simulations are given to illustrate availability and robustness of our algorithm

    Underdetermined blind separation by combining sparsity and independence of sources

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    In this paper, we address underdetermined blind separation of N sources from their M instantaneous mixtures, where N>M , by combining the sparsity and independence of sources. First, we propose an effective scheme to search some sample segments with the local sparsity, which means that in these sample segments, only Q(Q < M) sources are active. By grouping these sample segments into different sets such that each set has the same Q active sources, the original underdetermined BSS problem can be transformed into a series of locally overdetermined BSS problems. Thus, the blind channel identification task can be achieved by solving these overdetermined problems in each set by exploiting the independence of sources. In the second stage, we will achieve source recovery by exploiting a mild sparsity constraint, which is proven to be a sufficient and necessary condition to guarantee recovery of source signals. Compared with some sparsity-based UBSS approaches, this paper relaxes the sparsity restriction about sources to some extent by assuming that different source signals are mutually independent. At the same time, the proposed UBSS approach does not impose any richness constraint on sources. Theoretical analysis and simulation results illustrate the effectiveness of our approach

    Futures Studies in the Interactive Society

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    This book consists of papers which were prepared within the framework of the research project (No. T 048539) entitled Futures Studies in the Interactive Society (project leader: Éva Hideg) and funded by the Hungarian Scientific Research Fund (OTKA) between 2005 and 2009. Some discuss the theoretical and methodological questions of futures studies and foresight; others present new approaches to or procedures of certain questions which are very important and topical from the perspective of forecast and foresight practice. Each study was conducted in pursuit of improvement in futures fields

    Technology transfer: Transportation

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    The successful application of aerospace technology to problems related to highways and rail and rapid transit systems is described with emphasis on the use of corrosion resistant paints, fire retardant materials, and law enforcement. Possible areas for the use of spinoff from NASA technology by the California State Department of Corrections are identified. These include drug detection, security and warning systems, and the transportation and storage of food. A communication system for emergency services is also described

    COGNITIVE MULTI-USER FREE SPACE OPTICAL COMMUNICATION

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    Increasing deployment of terrestrial, aerial, and space-based assets designed with more demanding services and applications is dramatically escalating the need for high capacity, high data-rate, adaptive, and flexible communication networks. Cognitive, multi-user Free Space Optical Communication (FSOC) networks provide a solution to address these challenges. Such FSOC networks can potentially merge automation and intelligence, as well as offer the benefits of optical communication with enhanced bandwidth and data-rate over long communication networks. Extensive research has investigated various designs, techniques, and methods to enable desired FSOC systems. This dissertation reports the investigation and analysis of novel, state-of-the-art methodologies and algorithms for supporting cognitive, multi-user FSOC. This work details an investigation of the ability of diverse Optical-Multiple Access Control (O-MAC) techniques for performing multi-point communication. Independent Component Analysis (ICA) and Non-Orthogonal Multiple Access (NOMA) techniques were experimentally validated, both singularly and in a combined approach, in a high-speed FSOC link. These methods proved to successfully support multi-user FSOC when users share allocation resources (e.g., time, bandwidth, and space, among others). Additionally, transmission and channel parameters that can affect signal reconstruction performance were identified. To introduce cognition and flexibility into the network, the research reported herein details the use of several Machine Learning (ML) algorithms for estimating crucial parameters at the Physical Layer (PHY) of FSOC networks (e.g., number of transmitting users, modulation format, and quality of transmission [QoT]) for automatically supporting and decoding multiple users. In particular, a novel methodology based on a weighted clustering analysis for automatic and blind user discovery is presented in this work. Extensive experimental analysis was conducted under multiple communication scenarios to identify system performance and limitations. Experimental results demonstrated the ability of the proposed techniques to successfully estimate parameters of interest with high accuracy. Finally, this dissertation presents the design and testing of a modular, multiple node, high-speed, real-time Optical Wireless Communication (OWC) testbed, which provides a hardware and software platform for testing proposed methods and for further research development. This dissertation successfully proves the feasibility of cognitive, multi-user FSOC through the developed and presented methodologies, as well as extensive experimental analyses. The main strength of the research outcomes of this work consists of exploiting software solutions (e.g., O-MAC, signal processing, and ML techniques) to intelligently support multiple users into a single optical channel (i.e., same allocation resources). Accordingly, Size, Weight and Power (SWaP) requirement can be reduced while achieving an increased network capacity

    The ‘Wickedness’ of Governing Land Subsidence: Policy Perspectives From Urban Southeast Asia

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    Drawing on Jakarta, Metro Manila and Singapore as case studies, we explore the paradox of slow political action in addressing subsiding land, particularly along high-density urban coastlines with empirical insights from coastal geography, geodesy analysis, geology, and urban planning. In framing land subsidence as a classic ‘wicked’ policy problem, and also as a hybrid geological and anthropogenic phenomenon that is unevenly experienced across urban contexts, the paper uses a three-step analysis. First, satellite-derived InSAR maps are integrated with Sentinel-1A data in order to reveal the socio-temporal variability of subsidence rates which in turn pose challenges in uniformly applying regulatory action. Second, a multi-sectoral mapping of diverse policies and practices spanning urban water supply, groundwater extraction, land use zoning, building codes, tenurial security, and land reclamation reveal the extent to which the broader coastal governance landscape remains fragmented and incongruous, particularly in arresting a multi-dimensional phenomenon such as subsidence. Finally, in reference to distinct coastal identities of each city–the ‘Sinking Capital’ (Jakarta), ‘Fortress Singapore’, and the ‘Disaster Capital’ (Manila) the paper illustrates how land subsidence is portrayed across the three metropolises in markedly similar ways: as a reversible, quasi-natural, and/or a highly individualized problem
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