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  • Artificial Intelligence - AI
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Artificial Neural Network (ANN) A. Introduction to neural networks B. ANN architectures • Feedforward networks • Feedback networks • Lateral networks C. Learning methods • Supervised learning • Unsupervised learning • Reinforced learning D. Learning rule on supervised learning • Gradient descent, • Widrow-hoff (LMS) • Generalized delta • Error-correction E. Feedforward neural network with Gradient descent optimization

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Introduction to neural networks Definition: the ability to learn, memorize and still generalize, prompted research in algorithmic modeling of biological neural systems Do you think that computer smarter than human brain? “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 - which form integral parts of human intelligence”…(Alan intelligence”…( Turing, 1950) ---Human brain has the ability to perform tasks such as pattern recognition, perception and motor control much faster than any computer---

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Facts of Human Brain (complex, nonlinear and parallel computer) • • • • • • • • The brain contains about 1010 (100 billion) basic units called neurons Each neuron connected to about 104 other neurons Weight: birth 0.3 kg, adult ~1.5 kg Power consumption 20-40W (~20% of body consumption) Signal propagation speed inside the axon ~90m/s in ~170,000 Km of axon length for adult male Firing frequency of a neuron ~250 – 2000Hz Operating temperature: 37±2oC Sleep requirement: average 7.5 hours (adult) Intel Pentium 4 1.5GHz Number of transistors 4.2x107 Power consumption up to 55 Watts 0.1 kg cartridge w/o Weight fans, 0.3 kg with fan/heatsink Maximum firing 1.5 GHz frequency Normal operating 15-85°C temperature 0 (if not overheated/ Sleep requirement overclocked) Processing of complex if can be done, takes a stimuli long time

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Biological neuron • • • • • • • • Soma: Nucleus of neuron (the cell body) process the input Dendrites: long irregularly shaped filaments attached to the soma – input channels Axon: another type link attached to the soma – output channels Output of the axon: voltage pulse (spike) that lasts for a ms Firing of neuron – membrane potential Axon terminates in a specialized contact called the synaptic junction – the electrochemical contact between neurons The size of synapses are believed to be linked with learning Larger area: excitatory—smaller area: inhibitory

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