Explore fundamental concepts and properties of even and odd signals, including their mathematical behavior, graphical characteristics, and real-world applications. Sharpen your understanding of signal symmetry and its role in engineering and mathematics with these carefully crafted medium-difficulty questions.
Which of the following signals is considered an even signal based on its mathematical property?
Explanation: An even signal satisfies the condition f(-t) = f(t) for all t, which is true for f(t) = t^2 since squaring -t gives the same result as squaring t. The function e^t is neither even nor odd because e^{-t} does not equal e^t or -e^t. The function sin(t) is an odd function, as sin(-t) = -sin(t), and t^3 is also odd since (-t)^3 = -t^3. Only t^2 among the options is even.
If a signal satisfies the condition f(-t) = -f(t) for all t, which statement about the signal's symmetry is correct?
Explanation: A function or signal that satisfies f(-t) = -f(t) is called odd and has symmetry about the origin, meaning its graph is rotated 180 degrees about the origin. Even functions are symmetric about the y-axis, which requires f(-t) = f(t). Periodicity and lack of symmetry are unrelated here, making these options incorrect. Therefore, 'odd and symmetric about the origin' is correct.
What type of signal results if you add an even signal and an odd signal together (e.g., f_e(t) + f_o(t))?
Explanation: The sum of an even and an odd signal is generally neither even nor odd because their symmetry properties cancel each other out except in special cases (such as one of them being zero). The sum will not always be even or odd, and the property of being periodic with period 2 is unrelated to evenness or oddness. The most accurate answer is that in general, the signal is neither even nor odd.
When graphing an even signal, which visual property distinguishes it from an odd signal?
Explanation: Even signals are defined by their symmetry with respect to the y-axis, meaning the left side of the graph mirrors the right. Odd signals have origin symmetry, not y-axis symmetry. Passing through the origin is not a defining trait, as even functions might not pass through the origin. Periodicity and symmetry across the line y = x are unrelated to the definition of an even signal.
Why is it useful to decompose a complex signal into its even and odd components in signal processing?
Explanation: Decomposing signals into even and odd parts allows for easier mathematical analysis, especially in Fourier and Laplace transforms, as many properties depend on symmetry. While this may sometimes reduce computation, it does not guarantee computational efficiency. Decomposition does not directly eliminate noise or make a signal periodic, so these options do not apply. The main benefit is the simplification of analysis and the insight into the signal’s structure.