Autocorrelation measures periodic self-similarity in a signal across time delays.

Evidence

Autocorrelation is a check for repetition or self-similarity. Does the signal, which might look quite unruly, tend in fact to repeat patterns at regular intervals? For example, if there is a large positive fluctuation in s(t) at some time t, does there tend to be another a time τ later? Or, is it anticorrelated at time τ: most often s(t + τ) has the opposite sign as does s(t). The product s(t)s(t + τ) would be most often negative and 〈s(r)s(t + τ)〉 would be negative for that value of the time delay τ. If s(t) and s(t + τ) are uncorrelated, so that s(t)s(t + τ) is as likely positive as negative, the average and thus c(τ) will be zero at time τ. — Eric J. Heller, Why You Hear What You Hear- An…, 369

Categorization

• DEFINE: Defines autocorrelation as a repetition/self-similarity check across time delays, with the three outcome cases (correlated, anticorrelated, uncorrelated) clearly laid out.
• corroborated: 2 independent passages support this claim — Eric J. Heller, Why You Hear What You Hear- An…, 369
• XREF: connects to: Impulse velocity response serves as a ready-made autocorrelation; Time-delayed sound self-addition imposes spectral notches via autocorrelation; Autocorrelation discriminates echoes from genuine distinct sounds. (+10 more)

Broader Connections

• Tiny periodic signals can be recovered from heavy noise via autocorrelation #expands (0.95) — Eric J. Heller, Why You Hear What You Hear- An…, 432
• Autocorrelation predicts pitch yet met lukewarm reception #expands (0.85) — Eric J. Heller, Why You Hear What You Hear- An…, 2085
• Qualitative pitch mirrors the qualitative nature of autocorrelation peaks #exemplifies (0.80)