Consider an industrial automation and control application. It has a normalized bi-folded dataset comprises of pressure and temperature, as shown. The model has a corresponding bi-state output ('1' motor on, '0' motor off). A Single Layer Perceptron (SLP) is required to be designed to classify a two-dimensional data. You are given with the following four patterns (p) along with their target classes (t). Output (t) Input (x) x x t -1 -1 1 -1 1 0 -1 0 1 Given that the perceptron has the following initial weights, learning rate, and threshold, respectively. Wij= [1 0.2], a=0.1, and 0=-0.25. a. Construct the neural schema for SLP-ANN with labeled weights and neurons. Also plot the patterns in a two-dimensional space with the decision boundary. b. Compute the actual output, error, correct percentage recognition, and trained weights for ONE epochs ONLY.