RAID: a neural network for rapid event identification in photon counting intensified CCDs

A computational system based on a synchronous feedback neural network for the on-line event processing of a photon counting intensified CCD detector is presented. The hardware prototype, implemented by means of FPGA technology, consists of 5x5 and is a b k to identify photon events against spurious and/or noise events. It shows a high level of flexiliility, which is essential in the characterization phase of the detector. It allows to implement different kinds of neurons, that is having different output functions and internal architectures, and to run actual, as well as virtual, networks of neurons.

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An FPGA-based on-line neural system in photon counting intensified imagers for space applications

Alderighi

D'Angelo²,

Sechi³

et al.

Proceedings of 3rd International Conference on Algorithms and Architectures for Parallel Processing

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A reconfigurable neural network for pattern identification in CCD-based detectors

Alderighi

D'Angelo²,

Gummati³

et al.

IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings

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RAID: a neural network for rapid event identification in photon counting intensified CCDs

Cited by 2 publications

References 4 publications

An FPGA-based on-line neural system in photon counting intensified imagers for space applications

An FPGA-based on-line neural system in photon counting intensified imagers for space applications

A reconfigurable neural network for pattern identification in CCD-based detectors

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