Impulse velocity response serves as a ready-made autocorrelation

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 (#expands, via linked claim)

Categorization

• XREF: connects to: Velocity response is the convenient quantity for impulse power; Autocorrelation measures periodic self-similarity in a signal across time delays. — Eric J. Heller, Why You Hear What You Hear- An…, 369; Tiny periodic signals can be recovered from heavy noise via autocorrelation — Eric J. Heller, Why You Hear What You Hear- An…, 432 (+3 more)

Related

• Autocorrelation measures periodic self-similarity in a signal across time delays. (similarity 0.91)
• A signal’s autocorrelation is a cosine sum over its sinusoidal partials. (similarity 0.86)
• A finite-length burst yields a short-lived autocorrelation that vanishes beyond its duration (similarity 0.85)
• Tiny periodic signals can be recovered from heavy noise via autocorrelation (similarity 0.85)
• Autocorrelation discriminates echoes from genuine distinct sounds. (similarity 0.85)
• Pitch perception corresponds to peaks in the autocorrelation function (similarity 0.84)
• Autocorrelation reveals a signal’s fundamental periodicity through periodic peaks. (similarity 0.83)
• Autocorrelation is mathematically equivalent to the power spectrum (similarity 0.83)
• Autocorrelation measures how a signal correlates with itself shifted in time (similarity 0.82)
• Autocorrelation nearly perfectly predicts perceived residue pitch across a range of tone series. (similarity 0.82)
• Autocorrelation, proposed in 1951, remains essential to pitch perception theory (similarity 0.82)
• Natural measurements correlate over time because dynamics persist (similarity 0.82)
• Time-delayed sound self-addition imposes spectral notches via autocorrelation (similarity 0.81)
• Pitch is a human synthesis keyed to autocorrelation, not pure physics (similarity 0.81)
• Autocorrelation averages products across all shifted pairs (similarity 0.81)

Broader Connections

• Frequency, phase, and impulse responses are interchangeable transforms of each other #corroborates (0.85)
• Velocity response is the convenient quantity for impulse power #expands (0.82)
• Autocorrelation measures periodic self-similarity in a signal across time delays. #expands (0.80) — Eric J. Heller, Why You Hear What You Hear- An…, 369
• Tiny periodic signals can be recovered from heavy noise via autocorrelation #exemplifies (0.75) — Eric J. Heller, Why You Hear What You Hear- An…, 432
• Pitch perception corresponds to peaks in the autocorrelation function #corroborates (0.72) — Eric J. Heller, Why You Hear What You Hear- An…, 2033