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Syllabus | B.Tech-Computer Science & Engineering | Neural Networks Lab

  Neural Networks Lab Learning Schedule
L T P C
Pre-requisites: C++ 0 0 2 1

 

COURSE OBJECTIVES

The objective of this course is to

  1. make students familiar with basic concepts and tool used in neural networks
  2. teach students structure of a neuron including biological and artificial
  3. teach learning in network (Supervised and Unsupervised)
  4. teach concepts of learning rules.

 

COURSE OUTCOMES

On completion of this course, the students will be able to

  1. superior for cognitive tasks and processing of  sensorial data such as vision, image- and speech recognition, control, robotics, expert systems
  2. design single and multi-layer feed-forward neural networks
  3. understand  supervised and unsupervised learning concepts & understand unsupervised learning using Kohonen networks
  4. understand training of recurrent Hopfield networks and associative memory concepts.

 

LIST OF EXPERIMENTS

  1. Study of Matlab
  2. (a) Write a program to perform basic operations in Matlab

(b) To perform matrix operations in Matlab

  1. (a) Introduction to script file in Matlab

(b) Write a program to calculate the factorial of a number by creating a script file by using while loop

(c) Write a program in Matlab to find the factorial by creating a function file by using for loop

  1. (a) Write a program in Matlab to plot multiple curves in single plot by creating a script file

(b) Write a program in Matlab for plotting multiple curves in single figure

  1. (a) Write a program in Matlab to plot Activation function used in neural network

(b) Write a program in Matlab to plot piecewise continuous activation function (threshold and signum function in neural network)

  1. (a) To realize gates using Mcculloh Pitt model in Matlab

(b) Write a program to implement XOR gate using Mcclloh-Pitts neuron

  1. (a) Write a program to create the Perceptron using GUI in Matlab

(b) Write a program in Matlab to create `Perceptron using commands

  1. (a) Write a program in Matlab to classify the Classes using Perceptron

(b) Write a program in Matlab for Pattern Classification using Perceptron network

  1. Write a program in Matlab for creating a Back Propagation Feed-forward neural network
  2. To design a Hopfield Network which stores 4 vectors
  3. Write a program to illustrate how the perception learning rule works for non-linearly separable problems
  4. Write a program to illustrate Linearly non-separable vectors

 

ADMISSIONS 2021