This paper presents an evaluation of several types of neural networks for object recognition by means of ultrasonic sensors. Initially, in order to obtain information from the ultrasonic signal, a parametric method is proposed and a set of features is extracted from the ultrasonic echo envelope. Then, it is necessary to evaluate how much information is provided for each characteristic obtained. Therefore, it has been necessary to carry out an analysis in order to detect the most relevant features. Results about information provided for each feature are presented by order of preference. Subsequently, using these features extracted from the echo signal, an experimental set‐up has been carried out in order to highlight the capabilities of different types of neural networks with this information. Finally, results obtained from experimental tests are presented, and the pattern recognition capabilities of each neural network type, using the selected features, are shown.
Llata, J.R., Sarabia, E.G. and Oria, J.P. (2001), "Pattern recognition with ultrasonic sensors: a neural networks evaluation", Sensor Review, Vol. 21 No. 1, pp. 45-51. https://doi.org/10.1108/02602280110365653Download as .RIS
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