Publication | Closed Access
An artificial neural minimum-variance estimator
11
Citations
17
References
1988
Year
Artificial IntelligenceEngineeringMachine LearningNeural Networks (Machine Learning)Value Function ApproximationArtificial Neural NetsRecurrent Neural NetworkSocial SciencesQuadratic Programming ProblemSystems EngineeringEstimation TheoryStatisticsLinear OptimizationRecurrent NetNeural Networks (Computational Neuroscience)Statistical Learning TheoryEvolving Neural NetworkComputational NeuroscienceNeuronal Network
Results are presented of a study into one aspect of the application of artificial neural nets to the continuous working mode. For the proposed configuration, the authors give sufficient conditions for the existence and uniqueness of the steady-state solution. They show the feasibility of the choice of the proposed recurrent net for solving a quadratic programming problem using an analog working mode. The authors validate the theory for minimum-variance deconvolution.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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