Following the example in Section 3.10-1, numerically calculate the Fourier transform of the following signals and compare them with the theoretical results in frequency domain:
(a) The signal waveform of Figure P3.3-1a
(b) The signal waveform of Figure P3.3-1b
(d) The signal waveform of Figure P3.3-4
Following the example in Section 3.10-1, numerically calculate the Fourier transform of the following signals and...
2.10-3 Using direct integration, numerically derive and plot the exponential Fourier series coefficients of the following periodic signals: (a) The signal waveform of Figure P2.1-5 (b) The signal waveform of Figure P2.1-10(a) (c) The signal waveform of Figure P2.1-10(f) 2.10-4 Using the FFT method, repeat Problem 2.10-3. e P2.1-5 g (t) -6 4 -8 2.10-3 Using direct integration, numerically derive and plot the exponential Fourier series coefficients of the following periodic signals: (a) The signal waveform of Figure P2.1-5 (b)...
Q4) Calculate the Fourier transform of the following time domain signals. Use the properties of the Fourier transform found in the "Properties of Fourier Transforms" table in textbook and the "Famous Fourier Transforms Table" in textbook instead of direct integration as much as possible to simplify your calculation wherever appropriate: 2-2
1-Can we calculate the Fourier Transform for a function represented by Fourier Series? Elaborate. 2-What happens if we sample with a frequency that is less than half the maximum frequency of the sampled signal? 3-Describe in your words what is Fourier Series and its relation to periodic signals. Mention whether it is a time domain or frequency domain representation
1. Draw frequency domain representations (sketches of the real and imaginary parts of the Fourier transform) for both cos(2*pi*fc*t) and sin(2*pi*fc*t), for a carrier waveform. ____________________ Now suppose we have a sinusoidal signal of frequency fi, where fi << fc. Let the signal be m(t)=cos(2*pi*fi*t) and the carrier be cos(2*pi*fc*t). Say we mix m(t) up to carrier frequency fc when we multiply m(t) by the carrier to create the modulated signal, s(t) = m(t) * cos(2*pi*fc*t). Draw the real part...
3) (Fourier Transforms Using Properties) - Given that the Fourier Transform of a signal x(t) is X(f) - rect(f/ 2), find the Fourier Transform of the following signals using properties of the Fourier Transform: (a) d(t) -x(t - 2) (d) h(t) = t x( t ) (e) p(t) = x( 2 t ) (f) g(t)-x( t ) cos(2π) (g) s(t) = x2(t ) (h)p()-x(1)* x(t) (convolution) 3) (Fourier Transforms Using Properties) - Given that the Fourier Transform of a signal...
This is taken from Section 4.6, "Amplitude Modulation and the Continuous-Time Fourier Transform," in the course text Computer Explorations in signals and systems by Buck, Daniel, Singer, 2nd Edition. I need the answers for the basic and intermediate questions. 4.6 Amplitude Modulation and the Continuous-Time Fouriei Transform This exercise will explore amplitude modulation of Morse code messages. A simple ampli tude modulation system can be described by x(t) = m(t) cos(Crfot), (4.13) where m(t) is called the message waveform and...
(a) Determine the Fourier transform of x(t) 26(t-1)-6(t-3) (b) Compute the convolution sum of the following signals, (6%) [696] (c) The Fourier transform of a continuous-time signal a(t) is given below. Determine the [696] total energy of (t) 4 sin w (d) Determine the DC value and the average power of the following periodic signal. (6%) 0.5 0.5 (e) Determine the Nyquist rate for the following signal. (6%) x(t) = [1-0.78 cos(50nt + π/4)]2. (f) Sketch the frequency spectrum of...
2) (Fourier Transforms Using Properties) - Given that the Fourier Transform of x(t) e Find the Fourier Transform of the following signals (using properties of the Fourier Transform). Sketch each signal, and sketch its Fourier Transform magnitude and phase spectra, in addition to finding and expression for X(f): (a) x(t) = e-21,-I ! (b) x(t)-t e 21 1 (c) x(t)-sinc(rt ) * sinc(2π1) (convolution) [NOTE: X(f) is noLI i (1 + ㎡fy for part (c)] 2) (Fourier Transforms Using Properties)...
f) Calculate the coefficients of the trigonometric form of the Fourier series numerically in MATLAB and graphically represent the one-sided spectrum (width and phase) frequency for n up to 10 compared to the analytics results. g) From the coefficients of the trigonometric form of the Fourier series , calculate the coefficients of the exposure series and present the two-sided spectrum (width and phase) frequency. h) Find the average and active value of the signal from the Fourier expansion. i) Check...
Problem 3.10: Compute the Fourier transform of each of the following signals. si(t) = [e-ot cos(wot)]u(t), a > 0; zz(t) = e34 sin(24); 13(t) = e T -00 X5(t) = [te-2+ sin(4t)]u(t);