Biologically Inspired Signal Processing for Chemical Sensing

1. Front Matter

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2. Biological Olfaction

   1. Front Matter

      Pages 1-1

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   2. “Sloppy Engineering” and the Olfactory System of Insects

      • Thomas Nowotny

      Pages 3-32

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   3. From ANN to Biomimetic Information Processing

      • Anders Lansner, Simon Benjaminsson, Christopher Johansson

      Pages 33-43

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   4. The Sensitivity of the Insect Nose: The Example of Bombyx Mori

      • Karl-Ernst Kaissling

      Pages 45-52

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   5. Multivariate Analysis of the Activity of the Olfactory Bulb

      • I. Montoliu, K. C. Persaud, M. Shah, S. Marco

      Pages 53-72

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3. Artificial Olfaction and Gustation

   1. Front Matter

      Pages 73-73

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   2. Improved Odour Detection through Imposed Biomimetic Temporal Dynamics

      • Tim C. Pearce, Manuel A. Sánchez-Montañés, Julian W. Gardner

      Pages 75-91

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   3. Relating Sensor Responses of Odorants to Their Organoleptic Properties by Means of a Biologically-Inspired Model of Receptor Neuron Convergence onto Olfactory Bulb

      • Baranidharan Raman, Ricardo Gutierrez-Osuna

      Pages 93-108

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   4. A Novel Bio-inspired Digital Signal Processing Method for Chemical Sensor Arrays

      • Eugenio Martinelli, Francesca Dini, Giorgio Pennazza, Maurizio Canosa, Arnaldo D’Amico, Corrado Di Natale

      Pages 109-120

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   5. Monitoring an Odour in the Environment with an Electronic Nose: Requirements for the Signal Processing

      • A. -C. Romain, J. Nicolas

      Pages 121-135

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   6. Multivariate Calibration Model for a Voltammetric Electronic Tongue Based on a Multiple Output Wavelet Neural Network

      • R. Cartas, L. Moreno-Barón, A. Merkoçi, S. Alegret, M. del Valle, J. M. Gutiérrez et al.

      Pages 137-167

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4. Back Matter

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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.

• Base
• Computational Intelligence
• Data Processing
• Sensor
• Signal Processing
• biologically inspired
• cognition
• environment
• information processing
• model
• neural network

• Departament d’Electronica, Universitat de Barcelona , Barcelona, Spain

  Agustín Gutiérrez

• Departament d’Electronica, Universitat de Barcelona, Barcelona, Spain

  Santiago Marco

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