Autonomous Defensive Space Control via On-Board Artificial Neural Networks von Manor, Michael T: New (2012)

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Bibliografische Details

Titel: Autonomous Defensive Space Control via On-Board Artificial Neural Networks
Verlag: Biblioscholar
Erscheinungsjahr: 2012
Sprache: Englisch
ISBN-10: 1288331029
ISBN-13: 9781288331024
Einband: Softcover
Zustand: New

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Inhaltsangabe

Future advances in neural network technology, coupled with increased computer processor capability, may create an opportunity to develop systems that enable satellites to autonomously differentiate, detect and defend against attacks. The Air Force should take advantage of this potential opportunity by investing the necessary resources for the development of space-based neural networks. An artificial neural network (ANN) or commonly just neural network (NN) is an artificial intelligence system created to mimic the ways and methods in which our own brains respond to and learn from inputted stimuli.1 Each of these networks consists of an array of neuron-like gates programmed to take action once a designated threshold is crossed.2 These ANN are adaptive, and learn through continued processing of inputted stimulus while developing a memory by storing the actions it takes in response to this stimulus.3 This memory gained through storing data enables ANNs to become somewhat autonomous over time because they have the ability to recall a given action taken based on a given input received.

Rese�a del editor

Future advances in neural network technology, coupled with increased computer processor capability, may create an opportunity to develop systems that enable satellites to autonomously differentiate, detect and defend against attacks. The Air Force should take advantage of this potential opportunity by investing the necessary resources for the development of space-based neural networks. An artificial neural network (ANN) or commonly just neural network (NN) is an artificial intelligence system created to mimic the ways and methods in which our own brains respond to and learn from inputted stimuli.1 Each of these networks consists of an array of neuron-like gates programmed to take action once a designated threshold is crossed.2 These ANN are adaptive, and learn through continued processing of inputted stimulus while developing a memory by storing the actions it takes in response to this stimulus.3 This memory gained through storing data enables ANNs to become somewhat autonomous over time because they have the ability to recall a given action taken based on a given input received.

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