SELF-ORGANIZING SENSORY MAPS IN ODOR CLASSIFICATION MIMICKING

被引：16

作者：

DAVIDE, FAM ^{[1
]}

DINATALE, C ^{[1
]}

DAMICO, A ^{[1
]}

机构：

[1] UNIV ROMA TOR VERGATA,DIPARTIMENTO INGN ELETTRON,I-00133 ROME,ITALY

来源：

BIOSENSORS & BIOELECTRONICS | 1995年 / 10卷 / 1-2期

关键词：

ARTIFICIAL OLFACTION; SELF-ORGANIZING MAP; VLSI NEURAL NETWORKS; HYBRID NEUROCOMPUTING; OPTICS AND MICROMACHINING;

D O I：

10.1016/0956-5663(95)96807-B

中图分类号：

Q6 [生物物理学];

学科分类号：

071011 ;

摘要：

A system for artificial olfaction is introduced, which is composed of a sensor array for gas sensing and a self-organising artificial neural network. A detailed reformulation of the most effective Self-Organising sensory Map (SOM)-based algorithms for odour classification and other applications is provided. An opto-electronic micromachined implementation of the neural network is introduced, which employs a novel hybrid mechanism for activating neural groups, avoiding fabricated cloning templates hardware.

引用

页码：203 / 218

页数：16

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