Pre-Processing |
In most applications, raw data cannot be applied to an ANN. One easy way to pre-process data is illustrated in the figure. The variable n is called the processing index. The processing index is always positive. From the xy plot, it can be seen that the pre-processing block compress the input signal x for some of its values, and expand x for other values. |
Problem 1 |
Crate a New Project called PrePro to plot the pre-processing function y = f(x) for a processing index n of: 0.25 and 4. (Use the Main file only option.) |
Solution 1 |
After editing the Main.lab file Run the code by pressing ![]() |
PrePro\Main.lab |
Vector x; x.CreateSeries(-1.0, 1.0, 200); Vector y025; Vector y4; y025.Create(200); y4.Create(200); int i = 0; for(i = 0; i<200; i++) { if (x[i] >= 0.0) { y025[i] = pow(x[i], 0.25); y4[i] = pow(x[i], 4.0); } else { y025[i] = -pow(-x[i], 0.25); y4[i] = -pow(-x[i], 4.0); } } |
Problem 2 |
(a) When is it appropriate to use a processing index that is less than one? (b) When is it convenient to use a processing index that is bigger than one? (c) What is the purpose of pre-processing the input data of an ANN? |
Problem 3 |
Consider x = sinc (w) and suppose that x is applied to a pre-processing module (a) Plot y for a processing index of n = 0.25 (ProcssSync.lab file). (b) Plot y for a processing index of n = 4 (ProcssSinc.lab file). |