Please show all the process using formulas belwo

Convolution . Definition: h(t) * x(t) = [_ h(t -T)x(T)dr = [_ h(r)x(t -T)dr . II (t) * 12(t) = 12(t) * 1(t) . ri(t) * (x2(t) * x3(t)) = (x1(t) * 12(t)) * ra(t)) associativety property of convolu- tion . II (t) * (12(t) + ra(t)) = =1(t) * 12(t) + m,(t) * 13(t) distributivity property of convolutionDiscrete Time . yln] = x[n] * h[n] >xx x[k]h[n - k] . Distributive Property x[n] * (h, [n] + hz[n]) = x[n] * h, [n] + x[n] * h2[n] . H(w) = [ h(t)e jutdt = [H(w)lejLH(w) frequency response of H . (Fourier transform of h(t) . y(t) = h(t) * x(t) = [_h(t -T)x()dr = [_ h(r)x(t -T)dr = h(t) * x(t) . H [ejt] = H(w)ejut . Y (w) = X (W) H(w)Fourier Transform and it's Inverse . x(t) = FIX(jw) = -x X (jw)ejut dw . X (jw) = F[x(t)] = [X x(t)e-jutdtCompute the convolution of each of the following pairs of signals a(t) and h(t) by calculating X (jw) and H(jw), using the convolution prop- erty, and inverse transforming. (a) x(t) = te-Hu(t), h(t) = e-du(t) (b) x(t) = te-tu(t), h(t) = te-du(t) (c) x(t) = e-tu(t), h(t) = eu(-t)