14 December 2006 A biologically inspired model for signal compression
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Abstract
A model of a biological sensory neuron stimulated by a noisy analog information source is considered. It is demonstrated that action-potential generation by the neuron model can be described in terms of lossy compression theory. Lossy compression is generally characterized by (i) how much distortion is introduced, on average, due to a loss of information, and (ii) the 'rate,' or the amount of compression. Conventional compression theory is used to measure the performance of the model in terms of both distortion and rate, and the tradeoff between each. The model's applicability to a number of situations relevant to biomedical engineering, including cochlear implants, and bio-sensors is discussed.
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Mark D. McDonnell, Derek Abbott, "A biologically inspired model for signal compression", Proc. SPIE 6416, Biomedical Applications of Micro- and Nanoengineering III, 64160Q (14 December 2006); doi: 10.1117/12.695646; https://doi.org/10.1117/12.695646
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KEYWORDS
Neurons

Image compression

Quantization

Distortion

Analog electronics

Sensors

Computer programming

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