Publication

---

Time encoding is a mechanism of mapping amplitude information into a time sequence. We show that multichannel time encoding using filter banks and integrate-and-fire neurons provides, under natural conditions, an invertible representation of information, i.e., a sensory stimulus can be recovered from its multidimensional spike train representation loss-free. We describe an algorithm for perfect stimulus recovery and derive conditions that guarantee its convergence.

Reference

---

@article{2005a,
  author = "Aurel A. Lazar",
  title = "Multichannel Time Encoding with Integrate-and-Fire Neurons",
  year = 2005,
  journal = "Neurocomputing",
  volume = 65-66,
  pages = "401-407",
  month = "Jun",
  keywords = "time encoding, integrate-and-fire neurons, filter banks, canonical models, perfect recovery"
}