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Module 2: Basic Ann Models: AIT 352 - Artificial Neural Networks Techniques by atulprakash01235 is a document available to read on EtoBox.

Module 2 of AIT 352 covers basic artificial neural network models, focusing on the McCulloch-Pitts neuron, its architecture, algorithm, and applications in implementing logical functions. It also discusses biases, thresholds, linear separability, and the Hebb Net learning rule. Key limitations of the M-P neuron include fixed weights, binary inputs, and inability to solve non-linearly separable problems like XOR.

Author

atulprakash01235

Language

EN