Consider the following cost (error) function: 2 .T where 2 is a constant, and 0.8182 0.8182 ,-10.8182 an xd 0.354 fk (1) Find the optimum value w for which E(w) reaches its minimum value. (2) Use the method of gradient descent to computer w recursively. Show the equations and then use a programming language, such as Matlab (note: you can use any kind of programming languages that you prefer) to plot the trajecto traced by the evolution of the weight vector w(n) Assume the initial condition of w is 0 0 n(0) = Considering the following two learning-rate parameter: a. =0.3 b. =1.0 Consider the following cost (error) function: 2 .T where 2 is a constant, and 0.8182 0.8182 ,-10.8182 an xd 0.354 fk (1) Find the optimum value w for which E(w) reaches its minimum value. (2) Use the method of gradient descent to computer w recursively. Show the equations and then use a programming language, such as Matlab (note: you can use any kind of programming languages that you prefer) to plot the trajecto traced by the evolution of the weight vector w(n) Assume the initial condition of w is 0 0 n(0) = Considering the following two learning-rate parameter: a. =0.3 b. =1.0