Detection of mines and minelike targets using principal component and neural-network methods
IEEE Transactions on Neural Networks
Signal detection using the radial basis function coupled map lattice
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Lidar detection of underwater objects using a neuro-SVM-based architecture
IEEE Transactions on Neural Networks
A Pyramidal Neural Network For Visual Pattern Recognition
IEEE Transactions on Neural Networks
Polytope ARTMAP: Pattern Classification Without Vigilance Based on General Geometry Categories
IEEE Transactions on Neural Networks
Neural Networks for Improved Tracking
IEEE Transactions on Neural Networks
A Hierarchical Graph Neuron Scheme for Real-Time Pattern Recognition
IEEE Transactions on Neural Networks
Relevance-Based Feature Extraction for Hyperspectral Images
IEEE Transactions on Neural Networks
Incremental Learning of Chunk Data for Online Pattern Classification Systems
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Analog implementation of a novel resistive-type sigmoidal neuron
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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A neural network (NN) was developed in order to increase the distance range of a phase-shift laser range finder and to achieve surface recognition, by using two photoelectrical signals issued from the measurement system. The NN architecture consists of a multilayer perceptron (MLP) with two inputs, three neurons in the hidden layer, and one output. Depending on the application, the NN output has to resolve the ambiguity due to phase-shift measurement by linearizing the inverse of the square law, or to indicate an output voltage corresponding to the tested surface. This embedded system dedicated to optoelectronic measurements was successfully tested with an analog NN, implemented in 0.35-µm complimentary metal-oxide-semiconductor (CMOS) technology, resulting in a threefold increase in the distance range with respect to the one limited by the phase-shift measurement, and by discriminating four types of surfaces (a plastic surface, glossy paper, a painted wall, and a porous surface), at a remote distance between the range finder and the target varying from 0.5 m up to 1.25 m and with a laser beam angle varying between-π/6 and π/6 with respect to the target. In this type of application, NN analog implementation provides many advantages, notably use of a small silicon area, low power consumption and no analog-to-digital conversions (ADCs). Nevertheless, digital implementation allows ease of conception and reconfigurability and an embedded weight and bias update. This paper presents the complete measurement system and a comparison between both types of implementation, by developing the advantages and drawbacks relative to each method. An optimized mixed architecture, using both techniques, is then proposed and discussed at the end of the paper.