BME253L - Fall 2025
Duke University
September 29, 2025
Review sinusoidal signals and their properties.
Root mean square (RMS) values of sinusoidal signals.
Complex numbers and Euler’s formula.
Phasor representation of sinusoidal signals.
\[ v(t) = V_{A} \sin(2 \pi f t + \phi) = V_{A} \sin(\omega t + \phi) = V_{A} \sin(2 \pi (t/T) + \phi) \]
\[ e^{j\theta} = \cos(\theta) + j \sin(\theta) \]
\[ v(t) = \text{Im} \{ V_{A} e^{j(\omega t + \phi)} \} \]
\[ v(t) = \text{Re} \{ V_{A} e^{j(\omega t + \phi - \pi/2)} \} \]
Why not just use average value?
The average value of a sinusoidal signal over one period is zero, regardless of frequency or amplitude.
This is because the positive and negative halves cancel out.
Therefore, average value is not a good measure of the signal’s power.
Does this make sense?
Instead, we use the root mean square (RMS) value.
\[ V_{RMS} = \sqrt{\frac{1}{T} \int_0^T [V_A \sin(\omega t + \phi)]^2 dt} \]
\[ P_R(t) = i_R v_R = \frac{v_R^2}{R} = \frac{V_A^2 \sin^2(\omega t + \phi)}{R} \]
Let’s calculate the average power over one period:
\[ P_{avg} = \frac{1}{T} \int_0^T P_R(t) dt = \frac{1}{T} \int_0^T \frac{V_A^2 \sin^2(\omega t + \phi)}{R} dt = \frac{V_A^2}{R} \cdot \frac{1}{T} \int_0^T \sin^2(\omega t + \phi) dt \]
Since the integral of \(\sin^2\) over one period is \(T/2\), we have:
\[ P_{avg} = \frac{V_A^2}{R} \cdot \frac{1}{T} \cdot \frac{T}{2} = \frac{V_A^2}{2R} \]
\[P_{avg} = \frac{V_{RMS}^2}{R}\]
Important
\(V_{RMS}\) is the equivalent DC voltage that would deliver the same average power to a resistive load as the AC voltage.
\[ \begin{gather} V(t) = V_A \cos(\omega t + \phi) \\ V_{RMS} = \sqrt{\frac{1}{T} \int_0^T V_A^2 \cos^2(\omega t + \phi) dt} \\ = V_A \sqrt{\frac{1}{T} \int_0^T \cos^2(\omega t + \phi) dt} \\ \textrm{Remember that:} \cos^2(x) = \frac{1 + \cos(2x)}{2} \\ = V_A \sqrt{\frac{1}{T} \int_0^T \frac{1 + \cos(2(\omega t + \phi))}{2} dt} \\ = V_A \sqrt{\frac{1}{T} \cdot \frac{T}{2}} \\ = \frac{V_A}{\sqrt{2}} \end{gather} \]
\[ V_{RMS} = \frac{V_A}{\sqrt{2}} \approx 0.707 V_A \]
What does this “look like”?