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- W50658105 abstract "An important goal of designing intelligent systems is to honor two principles of design: use of minimum information and use of minimum description length. If we can use only the features that are adequate for the task at hand, we move a few steps to honor the two stated principles. So feature selection is very important. Feature selection methods are primarily off-line in nature and they ignore the fact that the quality (importance) of a feature depends on the TOOL being used and the PROBLEM being solved. So we introduce a novel concept of ON-LINE feature selection where the system picks up the required features along with training of the system. In this context, we will explain three systems. The first system is designed for multi-layer perceptron type networks. The system is applicable to both classification and function approximation type problems. The second system is built based on a neuro-fuzzy framework for solving function approximation type problems. This system is then modified for dealing with classification type problems.There is another important related problem, selection of sensors. For many applications, the input comes from different sensors. For example, in case of an intelligent weld inspection system, the sensors could be X-ray image, Acoustic emission, eddy current and so on. The signal obtained from each sensor is used to compute several features; eg., the X-ray image can be used to compute several co-occurrence based features. In such cases, a more challenging problem comes - selection of sensors (in other words, selection of groups of features, where each group is computed using the signal obtained from a particular sensor). Clearly, if the number of necessary sensors can be reduced, the hardware cost of the system, the design complexity of the system and the cost (both in terms of time and money) of decision-making can be drastically reduced. We will discuss two systems for online sensor selection. The first approach is applicable to multi-layer perceptron type networks while the second method is for radial basis function type network." @default.
- W50658105 created "2016-06-24" @default.
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- W50658105 date "2003-01-01" @default.
- W50658105 modified "2023-09-26" @default.
- W50658105 title "On-line feature and sensor selection-the way to go" @default.
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