CSE

Neural Network CSE 6th Sem Syllabus for AKTU B.Tech 2019-20 Scheme (Departmental Elective-2)

Neural Network detail syllabus for Computer Science Engineering (CSE), 2019-20 scheme is taken from AKTU official website and presented for AKTU students. The course code (RCS-E22), and for exam duration, Teaching Hr/Week, Practical Hr/Week, Total Marks, internal marks, theory marks, and credits do visit complete sem subjects post given below.

For all other cse 6th sem syllabus for b.tech 2019-20 scheme aktu you can visit CSE 6th Sem syllabus for B.Tech 2019-20 Scheme AKTU Subjects. For all other Departmental Elective-2 subjects do refer to Departmental Elective-2. The detail syllabus for neural network is as follows.

Unit I

For the complete syllabus, results, class timetable and more kindly download iStudy. It’s a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.

Unit II

Data Processing Scaling: Normalization, Transformation (FT/FFT), principal component analysis, regression, co-variance matrix, Eigen values & Eigen vectors. Basic Models of Artificial neurons, activation Functions, aggregation function, single neuron computation, multilayer perception, least mean square algorithm, gradient descent rule, nonlinearly separable problems and bench mark problems in NN.

Unit III

Multilayered Network Architecture: Back propagation algorithm, heuristics for making BP-algorithm performs better. Accelerated learning BP (like recursive least square, quick prop, RPROP algorithm), approximation properties of RBF networks and comparison with multilayer perceptron.

Unit IV

For the complete syllabus, results, class timetable and more kindly download iStudy. It’s a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.

Unit V

Complex Valued NN and Complex Valued BP: Analyticity of activation function, application in 2D information processing. Complexity analysis of network models. Soft computing. Neuro-Fuzzy-genetic algorithm Integration

Reference Books:

  1. 1.J.A. Anderson, An Introduction to Neural Networks, MIT
  2. Hagen Demuth Beale, Neural Network Design, Cengage Learning
  3. Laurene V. Fausett, “Fundamentals of Neural Networks : Architectures, Algorithms and Applications”, Pearson India
  4. Munesh Chandra Trivedi, NN Jani, Artificial Neural Network Technology, Khanna Publishing House
  5. Kosko, Neural Network and Fuzzy Sets, PHI .

For detail syllabus of all other subjects of B.Tech Cse, 2019-20 regulation do visit Cse 6th Sem syllabus for 2019-20 Regulation.

Don’t forget to download iStudy for the latest syllabus, results, class timetable and more.

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