Artificial neural networks 人工神经网络 Introduction
Artificial Neural Networks 人工神经网络 Introduction
Table of contents · Introduction to ANNs taxonomy eatures Learning Applications · Supervised anns Unsupervised anNs Examples Examples Applications Applications Further topics Further topi II 02/02/2021 Artificial Neural Networks
02/02/2021 Artificial Neural Networks - I 2 Table of Contents • Introduction to ANNs – Taxonomy – Features – Learning – Applications I • Supervised ANNs – Examples – Applications – Further topics II • Unsupervised ANNs – Examples – Applications – Further topics III
Contents -I Introduction to anns Processing elements (neurons) Architecture Functional taxonomy of anns Structural Taxonomy of ANNs Features Learning Paradigms Applications 02/02/2021 Artificial Neural Networks
02/02/2021 Artificial Neural Networks - I 3 Contents - I • Introduction to ANNs – Processing elements (neurons) – Architecture • Functional Taxonomy of ANNs • Structural Taxonomy of ANNs • Features • Learning Paradigms • Applications
The Biological Neuron The synapse Soma Axon Terminal button Dendrite Nucleus Synap Ne euro gap transmitters Terminal buttons Dentate Schematic of biological neuron 10 billion neurons in human brain 10 billion synapses in human brain Summation of input stimuli Chemical transmission and Spatial (signals) modulation of signals emporal (pulses) · Inhibitory synapses Threshold over composed inputs · Excitatory synapses Constant firing strength 02/02/2021 Artificial Neural Networks
02/02/2021 Artificial Neural Networks - I 4 The Biological Neuron • 10 billion neurons in human brain • Summation of input stimuli – Spatial (signals) – Temporal (pulses) • Threshold over composed inputs • Constant firing strength • billion synapses in human brain • Chemical transmission and modulation of signals • Inhibitory synapses • Excitatory synapses 6 10
Biological Neural Networks CEREBRAL CORTEX 10,000 synapses per neuron Computational power Ib connectivity · Plasticity new connections strength of connections modified Fig. 204 -CaL TYPE IN LATERS IV-VI Oy VISUAL SENSORY CORTE Infant, Golgi Explanation in text. (Combined from fgures by Cajal.) 02/02/2021 Artificial Neural Networks
02/02/2021 Artificial Neural Networks - I 5 Biological Neural Networks • 10,000 synapses per neuron • Computational power = connectivity • Plasticity – new connections (?) – strength of connections modified