A Study on Backpropagation in Artificial Neural Networks
Ch. Chandra Sekhar, P. Meghana
Abstract
Innovation assumes essential job nowadays in human life to limit the manual work. Execution and exactness with innovation will be high. The Backpropagation neural framework is multilayered, feedforward neural framework and is by a full edge the most extensively utilized. It is moreover seen as one of the least demanding and most wide systems used for managed planning of multilayered neural systems. Backpropagation works by approximating the non-direct association between the data and the yield by changing the weight regards inside. It can furthermore be summarized for the data that is rejected from the planning structures (perceptive limits).
Topics & Concepts
BackpropagationArtificial neural networkComputer scienceArtificial intelligenceFeedforward neural networkFeed forwardLimit (mathematics)Machine learningEngineeringControl engineeringMathematicsMathematical analysisArtificial Intelligence in HealthcareNeural Networks and ApplicationsFuzzy Logic and Control Systems