Method of measuring taste using two phase radial basis function neural networks, a taste sensor, and a taste measuring apparatus
First Claim
1. A computer-implemented method for measuring tastes, said method comprising the steps of:
- subjecting a test sample to measurements by sensors comprising electrodes, each sensor can quantify at least one component representing, individually or cooperatively, the taste of saltiness, sourness, sweetness, umami or bitterness, to obtain a response value from each sensor;
inputting each of the obtained response values into a first phase radial basis function neural network, which correlates each response value with a concentration of each of the components and calculates the concentration of each component from each response value;
inputting the calculated concentration of each component into a second phase radial basis function neural network, which correlates the calculated concentration of each component and the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans, to calculate the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans; and
outputting the intensities as the measured taste.
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Abstract
A method for measuring tastes, which can better simulate the human gustation than known methods, as well as a taste sensor, computer program and an apparatus for measuring tastes, is disclosed. In this method, data processing is carried out by a two-phase radial basis function neural network. That is, by sensors, each of which sensors can quantify at least one component representing, individually or cooperatively, the taste of saltiness, sourness, sweetness, umami or bitterness, to obtain a response value from each sensor, and each of the obtained response values is input to a first phase radial basis function neural network to calculate the concentration of each component from each response value. Then, the concentration of each component is fed into a second phase radial basis function neural network, which correlates the concentration of each component with the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans, to calculate the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans.
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Citations
9 Claims
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1. A computer-implemented method for measuring tastes, said method comprising the steps of:
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subjecting a test sample to measurements by sensors comprising electrodes, each sensor can quantify at least one component representing, individually or cooperatively, the taste of saltiness, sourness, sweetness, umami or bitterness, to obtain a response value from each sensor; inputting each of the obtained response values into a first phase radial basis function neural network, which correlates each response value with a concentration of each of the components and calculates the concentration of each component from each response value; inputting the calculated concentration of each component into a second phase radial basis function neural network, which correlates the calculated concentration of each component and the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans, to calculate the intensities of saltiness, sourness, sweetness, umami and bitterness sensed by humans; and outputting the intensities as the measured taste. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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Specification