EENG 582 Artificial Neural Networks
Neural Network Concepts: what is a neural network? biological neuron, artificial neuron, neural network topologies. Learning in Neural Networks: types of learning, learning rules, error correction learning, Hebbian learning, competitive learning, Boltzmann learning. Application Tasks: function approximation, classification, association, application examples. Feedforward Networks: perceptron, multi-layer perceptron, radial basis function network, self-organizing map. Feedback Networks: Hopfield network, Boltzmann machine, real-time recurrent network.
EENG 582 Yapay Sinir Ağları
Sinir Ağı Kavramları: Sinir ağı nedir? biyolojik nöron, yapay nöron, sinir ağı topolojileri. Sinir Ağlarında Öğrenme: öğrenme türleri, öğrenme kuralları, hata düzeltmeli öğrenme, Hebbian öğrenme, rekabetçi öğrenme, Boltzmann öğrenme. Uygulama Görevleri: fonksiyon yaklaşımı, sınıflandırma, ilişkilendirme, uygulama örnekleri. İleri Besleme Ağları: algılayıcı, çok katmanlı algılayıcı, radyal tabanlı işlev ağı, kendi kendini organize eden harita. Geri Besleme Ağları: Hopfield ağı, Boltzmann makinesi, gerçek zamanlı tekrarlayan ağ.
- Instructor: Hasan Amca
Continuous-time and discrete-time signals and systems. Linear time-invariant (LTI) systems: system properties, convolution sum and the convolution integral representation, system properties, LTI systems described by differential and difference equations. Fourier series: Representation of periodic continuous-time and discrete-time signals and filtering. Continuous time Fourier transform and its properties: Time and frequency shifting, conjugation, differentiation and integration, scaling, convolution, and the Parseval’s relation. Representation of aperiodic signals and the Discrete-time Fourier transform. Properties of the discrete-time Fourier transform.
Storage structures and memory allocations. Primitive data structures. Data abstraction and Abstract Data Types. Array and record structures. Sorting algorithms and quick sort. Linear & binary search. Complexity of algorithms. String processing. Stacks & queues; stack operations, implementation of recursion, polish notation and arithmetic expressions. Queues and their implementations. Dequeues & priority queues. Linked storage representation and linked-lists. Doubly linked lists and circular lists. Binary trees. Tree traversal algorithms. Tree searching. General trees. Graphs; terminology, Operation on graphs and traversing algorithms. (Prerequisite: EENG112)