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Kort version - Fuld version
Artificial Neural Network (Forår 2007) |
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| Kursuskode : | IANN-U01 | ||
| ECTS Point : | 7,5 | Status : | Tilvalg |
| Placering : | 5-7 semester | Timer pr. uge : | 4 |
| Længde : | 1 semester | Undervisningssprog : | Dansk hvis der ikke er engelsksprogede studerende tilstede |
| Hovedindhold : | Introduction to the principles of the human brain, neurons, dendrites, axom,…. Artificial Neural Network components: - Adaline, perceptron, multiplayer perceptrons - Linear models, estimation, regression, least square, LMS algorithm - Patterns recognition, classifiers, training parameters’ - Training algoritms, backpropagation,adaptive systems - Nonlinear models, perceptron, MLP, training, classification, error and stopcriterias - Function approximation with MLP, Radial Basis funcionc, vector support machines - Hebbian learning, Oja´s rule, anti-hebbian learning, Associate memory, winner-take-all network, adaptive resonance theory - Digital signal processing, time series, frequency domain, adaptive filters - Static versus Dynamic systems, time-delay neural network, gamma memory - Training and using recurrent network, feedback parameters, hopfield network, Grossbergs additive model - Introduction to pulsed neural network and related electronics |
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| Undervisningsform : | The curriculum is based on an interactive book – overview lessons will allow (groups of) the student to study the interactive sessions and perform the related simulation exercises. | ||
| Krævede forudsætninger : | Documented knowledge of math corresponding to DSM3/DSM4 Analogue or digital design equivalent to 4th semester level. |
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| Ansvarlig underviser : | Gert Hvedstrup Jensen
, ghje@dtu.dk |
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