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1. 发明申请

US20090234196A1 Method of taste measuring, taste sensosr therefor and taste measuring apparatus 有权
标题翻译：味道测量方法，味觉感官和味觉测量仪器
公开(公告)号：US20090234196A1
公开(公告)日：2009-09-17
申请号：US11920924
申请日：2006-05-22
申请人： Koji Suzuki , Saeko Ishihara , Atsushi Ikeda , Yoshio Araki , Kenichi Maruyama , Daniel Citterio , Masafumi Hagiwara
发明人： Koji Suzuki , Saeko Ishihara , Atsushi Ikeda , Yoshio Araki , Kenichi Maruyama , Daniel Citterio , Masafumi Hagiwara
IPC分类号： A61B5/00
CPC分类号： G01N33/02 , G01N33/14
摘要： 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.
摘要翻译：公开了一种用于测量口味的方法，其可以比已知方法更好地模拟人的气味，以及味道传感器，计算机程序和用于测量口味的装置。在这种方法中，数据处理由两阶段径向基函数神经网络进行。也就是说，通过传感器，每个传感器可以量化至少一个单独或协同地表示咸味，酸味，甜味，鲜味或苦味的味道的组分，以从每个传感器获得响应值，并且获得的所有反应值被输入到第一阶段径向基函数神经网络，以从每个响应值计算每个分量的浓度。然后，将每个组分的浓度进料到第二相径向基函数神经网络，其将每个组分的浓度与人感测到的咸味，酸味，甜味，鲜味和苦味的浓度相关联，以计算盐度的强度，酸味，甜味，鲜味和人感觉到的苦味。

2. 发明授权

US07899765B2 Method of measuring taste using two phase radial basis function neural networks, a taste sensor, and a taste measuring apparatus 有权
标题翻译：使用两相径向基函数神经网络测量味道的方法，味觉传感器和味觉测量装置
公开(公告)号：US07899765B2
公开(公告)日：2011-03-01
申请号：US11920924
申请日：2006-05-22
申请人： Koji Suzuki , Saeko Ishihara , Atsushi Ikeda , Yoshio Araki , Kenichi Maruyama , Daniel Citterio , Masafumi Hagiwara
发明人： Koji Suzuki , Saeko Ishihara , Atsushi Ikeda , Yoshio Araki , Kenichi Maruyama , Daniel Citterio , Masafumi Hagiwara
IPC分类号： G06E1/00
CPC分类号： G01N33/02 , G01N33/14
摘要： 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.
摘要翻译：公开了一种用于测量口味的方法，其可以比已知方法更好地模拟人的气味，以及味道传感器，计算机程序和用于测量口味的装置。在这种方法中，数据处理由两阶段径向基函数神经网络进行。也就是说，通过传感器，每个传感器可以量化至少一个单独或协同地表示咸味，酸味，甜味，鲜味或苦味的味道的组分，以从每个传感器获得响应值，并且获得的所有反应值被输入到第一阶段径向基函数神经网络，以从每个响应值计算每个分量的浓度。然后，将每个组分的浓度进料到第二相径向基函数神经网络，其将每个组分的浓度与人感测到的咸味，酸味，甜味，鲜味和苦味的浓度相关联，以计算盐度的强度，酸味，甜味，鲜味和人感觉到的苦味。

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