Sketch the function tri(t/4) * delta\'(t) = tri(t / 4)*delta\"(t) . Note that yo

Question

Sketch the function tri(t/4) * delta'(t) = tri(t / 4)*delta"(t) . Note that your answer will contain impulses (which you can show by appropriate arrows). what is the, value of delta(t - 2) delta(t - 3)? Sketch the periodic function tri(2t)* 1/2 comb (t/2). Sketch the periodic function tri(t/2)* comb(t) A continuous-time l TI system has impulse response h(t) = e-tu(t). What is the response from rest of this system to input x(t) = 2 delta(t - 2)? What is the response, from rest, to input x(t) = 2u(t - 2)? Indicate whether the system is causal or non-causal: h(t) = 3e-2tu(t) h(t) = rect(t - 1/2) h(t) = rect(t - 5) h(t) = 2rect(2t + 3) By means of the moving paper method, find the result of the numerical convolution (1 1 2 1}*{1 2 2}. Note the time origins. Prove that the two sequences {l 1 l} and {l -10 1-10 1....} are inverses of each other. Indicate which of the following properties characterize the Fourier transforms of the functions listed below: even, odd, even-real, even-imaginary, complex-valued, non-symmetric. Hermitian symmetry (select all that apply). exp(-x2) u(t) cos 2 pi 4t exp(j2t) sgn(t) The impulse response of a linear, time-invariant discrete-time system is the sequence {1 -1}. What is the step response of this system i.e.. the response to the D.T. input signal x[n] = u[n] ? What is the response of the system to input x[n] = u[n] - u[n - 5]?

Explanation / Answer

Linear discriminant analysis (LDA) and the related Fisher's linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification. LDA is closely related to ANOVA (analysis of variance) and regression analysis, which also attempt to express one dependent variable as a linear combination of other features or measurements.[1][2] In the other two methods however, the dependent variable is a numerical quantity, while for LDA it is a categorical variable (i.e. the class label). Logistic regression and probit regression are more similar to LDA, as they also explain a categorical variable. These other m

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