Transcription of Artificial Neural Network (ANN) - 熊本大学
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Artificial Neural Network (ANN) - 熊本大学
Artificial Neural Network (ANN)A. Introduction to Neural networksB. ANN architectures Feedforwardnetworks Feedback networks Lateral networksC. Learning methods Supervised learning Unsupervised learning Reinforced learningD. Learning rule on supervised learning Gradient descent, Widrow-hoff(LMS) Generalized delta Error-correctionE. Feedforwardneural Network with Gradient descent optimizationIntroduction to Neural networksDefinition: the ability to learn, memorize and still generalize, prompted research in algorithmic modeling of biological Neural systemsDo you think that computer smarter than human brain? While successes have been achieved in modeling biological Neural systems, there are still no While successes have been achieved in modeling biological Neural systems, there are still no solutions to the complex problem of modeling intuition, consciousness and emotion solutions to the complex problem of modeling intuition, consciousness a
form integral parts of human intelligence”…(Alan Turing, 1950)---Human brain has the ability to perform tasks such as pattern recognition, perception and motor control much faster than any computer---Facts of Human Brain ... evolutionary computing and swarm optimization.
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