Browsing by Subject "Neural networks (Computer science)"
Now showing items 1-20 of 20
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(Texas A&M University. Libraries, 1993)An adaptive hybrid learning procedure is proposed for change detection and on-line identification of nonstationary manufacturing processes. Sequential measurements in manufacturing systems and on-line measured signals in ...
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(Texas A&M University, 1993)Not available
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(Texas A&M University, 1992)Not available
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(Texas A&M University, 1991)Not available
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(Texas A&M University. Libraries, 1992)The microelectronic implementation of neural networks has received widespread attention over the last few years. However, the scale of the integration is still far below what microelectronics routinely offers in the ...
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(Texas A&M University, 1993)Not available
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(Texas A&M University, 1992)Not available
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(Texas A&M University, 1993)Not available
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(American Geophysical Union, 2013)River flow synthesizing and downscaling are required for the analysis of risks associated with water resources management plans and for regional impact studies of climate change. This paper presents a probabilistic model ...
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(Texas A&M University, 1992)Not available
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(Texas A&M University, 1990)Not available
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(Texas A&M University. Libraries, 1992)This research investigated a supervised intelligent control of a robot end-effector using an Artificial Neural Network system. This control system performs dexterous control of end-effector for grasping objects interacting ...
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(Texas A&M University, 1992)Not available
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(Texas A&M University, 1991)Not available
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(Texas A&M University. Libraries, 1993)The objective of this research is to develop a nonlinear empirical model structure and an associated parameter estimation algorithm based on artificial neural networks (ANNs), and to further use it for the identification ...
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(Texas A&M University. Libraries, 2019-05)Predicting the effects of Polypharmacy is a difficult task, and a great amount of money is spent annually remedying the effects of negative drug interactions arising from Polypharmacy. However, Machine Learning can be used ...
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(Texas A&M University. Libraries, 1990)A methodology was developed using neural network theory to predict the occurrence of out of control process parameter conditions in a composite board manufacturing facility. Three weeks of process parameter data were ...