Exercises Train a 3-input, 1-output artificial neuron to classify apples and ora

Question

Exercises Train a 3-input, 1-output artificial neuron to classify apples and oranges in a supervised scheme based on each of the three learning rules. Use five pairs of input training pattens, s and their coresponding target values , for e.g. (s, t) - 1. --1-1). Make a random initial assignment of the weights. Gannon University ECE 474/GECE 574 ANN Fall 2017 Dr. Ram Sundaram 2. After the training process is completed, test your neuron with arbitrary input patterns representing either or neither fruit. Report on the accuracy of classification in the case of each leaming rule. 3. Develop an artificial neural network which extends this simple classification problem to the case when more varieties of fruit must be handled (e.g. apples, oranges, bananas, mangoes, peaches, plums).

Explanation / Answer

At this stage, UE does not have any resource or channel available to inform network about its desire to connect to it so it will send its request over the shared medium. Now there are two possibilities at this stage, either there are many other UEs in the same area (same cell) sending same request in which there is also a possibility of collision among the requests coming from various other UEs. Such random access procedure is called contention based Random access procedure. In second scenario, network can inform UE to use some unique identity to prevent its request from colliding with requests coming from other UEs. The second scenario is called contention free or non contention based random access procedure.

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