Every AV system starts with a signal: a physical quantity — voltage, sound pressure, light intensity — that carries information over time. An analog signal represents that information as a continuously varying quantity: a microphone's output voltage rises and falls smoothly, matching the sound wave that produced it. A digital signal instead represents the same information as a sequence of discrete numbers, sampled at fixed intervals.
Converting analog to digital (A/D conversion) requires two decisions: how often to sample, and how precisely to measure each sample. Sampling rate is how many measurements are taken per second, measured in Hz. The Nyquist theorem states that to accurately reproduce a signal, you must sample at more than twice its highest frequency — this is why CD audio uses 44.1 kHz to capture frequencies up to ~20 kHz (the edge of human hearing), and why undersampling produces aliasing, a distortion where high frequencies fold back and appear as false low frequencies.
Bit depth (or resolution) is the second decision: how many discrete levels are used to represent each sample's amplitude. 16-bit audio has 65,536 possible levels; 24-bit has over 16 million. Higher bit depth reduces quantization error — the small rounding difference between the true analog value and its nearest digital level — and improves signal-to-noise ratio (SNR), usually expressed in decibels (dB).
AV technicians work in both worlds simultaneously: an analog microphone feeds a digital signal processor, which outputs to a digital display over HDMI, which may itself get converted back to analog for a legacy amplifier. Knowing where each conversion happens — and where it can introduce noise, latency, or loss — is the foundation everything else in this course builds on.