In this section, you will generate filtering results needed in a later section. Use the discrete-time...

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In this section, you will generate filtering results needed in a later section. Use the discrete-time convolution GUI, dconvdemo, to do the following: (a) Set the input signal to be r[n] = (0.9)" (u[n]u[n-10]). Use the "Exponential" signal type within Get x[n]. (b) Set the impulse response to be h[n] = [n] -0.98[n 1]. Once again, use the "Exponential" signal type within Get h[n]. (c) Illustrate the output signal y[n] and explain why it is zero for almost all points. Compute the numerical value of the last point in y[n], i.e., the one that is negative and non-zero. In this section, you will generate filtering results needed in a later section. Use the discrete-time convolution GUI, dconvdemo, to do the following: (a) Set the input signal to be r[n] = (0.9)" (u[n]u[n-10]). Use the "Exponential" signal type within Get x[n]. (b) Set the impulse response to be h[n] = [n] -0.98[n 1]. Once again, use the "Exponential" signal type within Get h[n]. (c) Illustrate the output signal y[n] and explain why it is zero for almost all points. Compute the numerical value of the last point in y[n], i.e., the one that is negative and non-zero.