In this paper we introduce and describe a novel generic and semiconductor-technology independent hardware development environment for a class of statistical signal- and imageprocessing models. The statistical signal-...
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In this paper we introduce and describe a novel generic and semiconductor-technology independent hardware development environment for a class of statistical signal- and imageprocessing models. The statistical signal- and imageprocessing approach under consideration formally adopts the Bayesian paradigm and uses discrete Markov Random Field (MRF) methods for the processing models to derive the joint distribution of signal- and image-processing problems by means of mathematically and computationally tractable conditional distributions. We experimentally demonstrate and prove the capabilities respectively the concepts of the proposed novel high-level design environment by detailed chip-layouts of different neighbourhood topologies and a single processing element of a MRF- architecture, which solves the imageprocessing problem of noise removing, restoration and intensity-level preserving.
In this paper we introduce and describe a generic and semiconductor-technology independent hardware development environment for a class of statistical signal- and imageprocessing models. The statistical signal- and i...
详细信息
In this paper we introduce and describe a generic and semiconductor-technology independent hardware development environment for a class of statistical signal- and imageprocessing models. The statistical signal- and imageprocessing approach under consideration formally adopts the Bayesian paradigm and uses discrete Markov random field (MRF) models for the processing models to derive the joint distribution of signal- and imageprocessing problems by means of mathematically and computationally tractable conditional distributions. We experimentally demonstrate and prove the capabilities respectively the concepts of the proposed high-level design environment by detailed chip layouts of different neighbourhood topologies and a single processing element of a MRF-architecture, which solves the imageprocessing problem of noise removing, restoration and intensity-level preserving.
In this paper, we propose a formal definition of the perception as a behavioral dynamical attraction basin. The perception is built from the integration of the sensori-motor flow. Psychological considerations and robo...
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