Spatial point processes.

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  • This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems. The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach.

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  • Estimating the directions of arrival (DOAs) of propagating planewaves is a requirement ina variety of applications including radar, mobile communications, sonar, and seismology. Due to its simplicity and high-resolution capability, ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) [18] has become one of the most popular signal subspace-basedDOAor spatial frequency estimation schemes. ESPRIT is explicitly premised on a point source model for the sources and is restricted to use with array geometries that exhibit so-called invariances [18]....

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  • The Digital Building Telecommunications Access Guideline Foreword Scope and Purpose Digital River The Process More information and comments Principle 1: Spatial Access and Design 1.1 Introduction 1.2 Communications Network Architectures 1.3 Telecommunications Service Entrance 1.4 Equipment Room 1.5 Backbone Pathways or Riser Shafts 1.6 Telecommunications closets (TC) 1.7 Horizontal pathways 1.8 Radio (Wireless) Facilities Provision 1.9 Standards & References Principle 2: Diversity 2.1 Building Entry Point (BEP) 2.2 Equipment Room 2.3 Riser Shafts 2.

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  • POINT AND SPATIAL IMAGE RESTORATION TECHNIQUES A common defect in imaging systems is unwanted nonlinearities in the sensor and display systems. Post processing correction of sensor signals and pre-processing correction of display signals can reduce such degradations substantially (1). Such point restoration processing is usually relatively simple to implement. One of the most common image restoration tasks is that of spatial image restoration to compensate for image blur and to diminish noise effects. References 2 to 6 contain surveys of spatial image restoration methods. ...

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  • Image registration is the process of spatially aligning two or more images of a scene. This basic capability is needed in various image analysis applications. The alignment process will determine the correspondence between points in the images, enabling the fusion of information in the images and the determination of scene changes. If identities of objects in one of the images are known, by registering the images, identities of objects and their locations in another image can be determined.

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  • IMAGE SAMPLING AND RECONSTRUCTION In digital image processing systems, one usually deals with arrays of numbers obtained by spatially sampling points of a physical image. After processing, another array of numbers is produced, and these numbers are then used to reconstruct a continuous image for viewing. Image samples nominally represent some physical measurements of a continuous image field, for example, measurements of the image intensity or photographic density. Measurement uncertainties exist in any physical measurement apparatus....

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  • Following the consensus points described above, we identify the specific benefits and beneficiaries that flow from the typical MA ecosystem services categories. We also identify the spatial data layers needed to map the location of these beneficiaries. In order to enable the ARIES modelling paradigm, all benefits must meet five requirements.

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