Assignment on Artificial Neural Network

Added on - 21 Apr 2020

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ARTIFICIALINTELLIGENCE
Table of Contents1.Artificial Neural Network................................................................................................22.Different Types of ANN Learning Algorithm................................................................23.Supervised learning..........................................................................................................23.1Multilayer perceptron..................................................................................................23.2Feed Forward Learning Algorithm..............................................................................44.Unsupervised learning......................................................................................................54.1Clustering algorithm....................................................................................................54.2Hebbian learning algorithm.........................................................................................74.3Radial basis function algorithm...................................................................................85.Reinforcement Learning Algorithm..............................................................................105.1Challenges.................................................................................................................106.Recall and precision algorithm......................................................................................106.1Mat lab execution......................................................................................................10
1.Artificial Neural Network (ANN)The neural networks are computing systems inspired by the biological neuralnetworks. An ANN is based on the collection of connected units which are called as artificialneurons. These neurons are typically organised in layers. An ANN learning algorithm isclassified into three main types, supervised learning, unsupervised learning and reinforcementlearning algorithms (Berlatsky, 2011).2.Different Types of ANN Learning AlgorithmAn ANN systems is classified into three main categories of neural networkalgorithms.Supervised learningUnsupervised learningReinforcement learningPart-A3.Supervised learningSupervised learning algorithm is divided into various types of learning algorithms.The most commonly used learning algorithms are listed belowMultilayer perceptron algorithmFeed forward algorithm3.1Multilayer perceptronMultilayer perceptron is a commonly used learning algorithm for mat lab software.The example for perceptron for the neural network systems is explained below:Sample code for perceptronx = [0 0 1 1; 0 1 0 1];t = [0 1 1 1];net = perceptron;net = train(net,x,t);view(net)y = net(x);
Figure1neural network design for perceptronExecution program for perceptronFigure2program execution for perceptronMat lab Execution for the performance of perceptronFigure3performance of perceptron
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