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In the displayed Fourier-series setup, $a_1$ is the coefficient for $\cos(t)$, which corresponds to the base frequency of $\frac{1}{2\pi}$ hertz. $a_2$ is the coefficient for $\cos(2t)$, corresponding to $\frac{1}{\pi}$ hertz.

Conditions: The function is represented in the displayed form with cosine coefficients $a_1, a_2, a_3$.; The comparison is about the coefficients multiplying $\cos(t)$ and $\cos(2t)$.

In the displayed Fourier-series setup, $a_1$ is the coefficient for $\cos(t)$, which corresponds to the base frequency of $\frac{1}{2\pi}$ hertz. $a_2$ is the coefficient for $\cos(2t)$, corresponding to $\frac{1}{\pi}$ hertz.

Conditions: The function is represented in the displayed form with cosine coefficients $a_1, a_2, a_3$.; The comparison is about the coefficients multiplying $\cos(t)$ and $\cos(2t)$.

Fourier series moves analysis from the time domain to the frequency domain by decomposing a periodic time signal $f(t)$ into a sum of sinusoids. Instead of looking at the function's values over time, the coefficients of the series reveal how much of each specific frequency is present, allowing for frequency-domain signal processing.

Conditions: The discussion concerns periodic functions represented by Fourier series.; Signal-processing applications are mentioned as motivation.

Fourier series moves analysis from the time domain to the frequency domain by decomposing a periodic time signal $f(t)$ into a sum of sinusoids. Instead of looking at the function's values over time, the coefficients of the series reveal how much of each specific frequency is present, allowing for frequency-domain signal processing.

Conditions: The discussion concerns periodic functions represented by Fourier series.; Signal-processing applications are mentioned as motivation.