Hearth / docsProject documentation

Reference

Flux Memory Lane

Look up syntax, contracts, layouts, algorithms, and exact behavior.

The flux lane is not a full tape or transformer model. It is a lighter path-dependent abstraction that gives rising and falling trajectories slightly different behavior. The purpose is to capture some of the audible benefits associated with hysteretic systems, such as attack rounding, denser lower mids, and small return-path differences, without the CPU cost of a high-detail physical model.

m[n]=m[n−1]+αdir(u[n]−m[n−1])m[n] = m[n-1] + \alpha_{\mathrm{dir}}(u[n] - m[n-1])
Direction-sensitive memory. The memory state approaches the current driven input with a rate selected from the current signal direction.

The lane stores a memory variable whose update rate depends on signal direction. A loop-area control blends the memory term into the nonlinear input, while a damping term prevents the memory from turning into an obvious resonant artifact.

yF[n]=fsoft(u[n]+hm[n])−ηm[n]y_F[n] = f_{\mathrm{soft}}(u[n] + h m[n]) - \eta m[n]
Flux output. The hysteresis-inspired memory bends the shaper input, then a damping term keeps the return path controlled.