Biologically Inspired Signal Processing for Chemical Sensing

This volume presents a collection of research advances in biologically inspired signal processing for chemical sensing. The book provides background on the olfactory system and some bio-inspired approaches to processing chemical sensor signals.

Biologically inspired approaches for artificial sensing have been extensively applied to different sensory modalities over the last decades and chemical senses have been no exception. The olfactory system, and the gustatory system to a minor extent, has been regarded as a model for the development of new artificial chemical sensing s- tems. One of the main contributions to this field was done by Persaud and Dodd in 1982 when they proposed a system based on an array of broad-selective chemical sensors coupled with a pattern recognition engine. The array aimed at mimicking the sensing strategy followed by the olfactory system where a population of bro- selective olfactory receptor neurons encodes for chemical information as patterns of activity across the neuron population. The pattern recognition engine proposed was not based on bio-inspired but on statistical methods. This influential work gave rise to a new line of research where this paradigm has been used to build chemical sensing instruments applied to a wide range of odor detection problems. More recently, some researchers have proposed to extend the biological inspiration of this system also to the processing of the sensor array signals. This has been mo- vated in part by the increasing body of knowledge available on biological olfaction, which has become in the last decade a focus of attention of the experimental neu- science community.

Presents recent research in Biologically inspired signal and data processing Includes supplementary material: sn.pub/extras

Inhalt
Biological Olfaction.- Sloppy Engineering and the Olfactory System of Insects.- From ANN to Biomimetic Information Processing.- The Sensitivity of the Insect Nose: The Example of Bombyx Mori.- Multivariate Analysis of the Activity of the Olfactory Bulb.- Artificial Olfaction and Gustation.- Improved Odour Detection through Imposed Biomimetic Temporal Dynamics.- Relating Sensor Responses of Odorants to Their Organoleptic Properties by Means of a Biologically-Inspired Model of Receptor Neuron Convergence onto Olfactory Bulb.- A Novel Bio-inspired Digital Signal Processing Method for Chemical Sensor Arrays.- Monitoring an Odour in the Environment with an Electronic Nose: Requirements for the Signal Processing.- Multivariate Calibration Model for a Voltammetric Electronic Tongue Based on a Multiple Output Wavelet Neural Network.