Upon completion of this exercise, you should be able to Obtain the output signal from...

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Upon completion of this exercise, you should be able to • Obtain the output signal from the convolution of the given signals. 2.1 Consider the two waveforms, h(t) and u(t), in Figure 1. Answer this exercise sequentially as laid out below. 1 0 h(t)=t+1 1 1 0 u(t)=u0(t) - u0(t-1) 1 Figure 1: Two rectangular waveforms h(t) and u(t). 2.1.1 Write a MATLAB code that creates the two rectangular pulse waveforms in Figure 1, h(t) and u(t). (6) 2.1.2 Then convolve the two waveforms h(t)*u(t) to produce the convolution waveform, y(t) = h(t) * u(t). (4) EVEDOISE #. ADDITIVE WHITE CALISSIAN NOISE 2.1.3 Plot the three waveforms (h(t), u(t), y(t)) in one graph, using subplot command in MATLAB. (6) 2.1.4 Comment on the output in terms of what you have learned in theory. (4) [20] Upon completion of this exercise, you should be able to • Obtain the output signal from the convolution of the given signals. 2.1 Consider the two waveforms, h(t) and u(t), in Figure 1. Answer this exercise sequentially as laid out below. 1 0 h(t)=t+1 1 1 0 u(t)=u0(t) - u0(t-1) 1 Figure 1: Two rectangular waveforms h(t) and u(t). 2.1.1 Write a MATLAB code that creates the two rectangular pulse waveforms in Figure 1, h(t) and u(t). (6) 2.1.2 Then convolve the two waveforms h(t)*u(t) to produce the convolution waveform, y(t) = h(t) * u(t). (4) EVEDOISE #. ADDITIVE WHITE CALISSIAN NOISE 2.1.3 Plot the three waveforms (h(t), u(t), y(t)) in one graph, using subplot command in MATLAB. (6) 2.1.4 Comment on the output in terms of what you have learned in theory. (4) [20]

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