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• W2027310802 abstract "This paper deals with a new design method for the analogue processing and generation of signals in measurement instruments. The method is based on the observation that in each processing procedure the operations to be performed on the input signal are represented by simple mathematical and control function blocks in a flow diagram. The paper shows how each block can be replaced by means of appropriately connected analogue neurones and the connections among them. The first step of the method concerns the transformation of basic mathematical and decision operations, included in the processing or generation of signals, into neural blocks. The second step concerns the opportune connection of the neural blocks. The third step concerns the optimisation of the connections between neural blocks by utilising the multiplication and adding properties of the neurones. The approach described is mainly devoted to the analogue neural network chip. Formulae are given for evaluating the uncertainty of each basic operation. Finally, applications of the proposed method, using programmable analogue neural network chips, to the instrumentation field are discussed." @default.
• W2027310802 created "2016-06-24" @default.
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• W2027310802 date "1999-07-01" @default.
• W2027310802 modified "2023-09-25" @default.
• W2027310802 title "Analogue neural network design for the processing of measurement signals" @default.
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• W2027310802 doi "https://doi.org/10.1016/s0263-2241(99)00013-5" @default.
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