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    USE OF HYDROXYOLEIC ACID AND RELATED COMPOUNDS AS FUNCTIONAL FOOD ADDITIVES
    4.
    发明公开
    USE OF HYDROXYOLEIC ACID AND RELATED COMPOUNDS AS FUNCTIONAL FOOD ADDITIVES 有权
    使用羟基油酸及相关化合物作为功能性食品添加剂的

    公开(公告)号：EP1696741A1

    公开(公告)日：2006-09-06

    申请号：EP03818931.2

    申请日：2003-11-28

    申请人： Universitat de les Illes Balears

    发明人： ESCRIBA RUIZ, Pablo, Vicente

    IPC分类号： A23L1/30 ,  A61K31/201

    CPC分类号： A61K31/201 ,  A23L33/12

    摘要： Use of hydroxyoleic acid and its analogous compounds as functional food additives. It describes the use of hydroxyoleic acid and its analogs of general formula I: COOH-CHR-(CH?2#191)?m#191-CH=CH-(CH?2#191)?n#191-CH?3#191, in which m and n have, independently, a valur of 0-15 and R can be any residue with molecular weight below 200 Da, in the manufacture and/or preparation of food additives and/or ingredients, dietary products, acceptable food forms and foods in general, focusing on improving parameters related to cardiovascular diseases, such as hypertension and obesity.

    ELEMENT FOR GENERATING STOCHASTIC SIGNALS, STOCHASTIC NEURON AND NEURAL NETWORK BASED ON SAID NEURON
    6.
    发明公开
    ELEMENT FOR GENERATING STOCHASTIC SIGNALS, STOCHASTIC NEURON AND NEURAL NETWORK BASED ON SAID NEURON 审中-公开

    公开(公告)号：EP4105834A1

    公开(公告)日：2022-12-21

    申请号：EP21754657.1

    申请日：2021-02-11

    申请人： Universitat de les Illes Balears

    发明人： ROSSELLO SANZ, Josep Lluis ,  FRANCO FRASSER, Christiam Camilo

    IPC分类号： G06N3/04

    摘要： The present invention consists of a stochastic signal generation element comprising a first binary to stochastic converter, which in turn comprises a first input for receiving a binary signal and a second input for receiving a random signal, and which is configured to convert said binary signal into a first stochastic signal using said random signal, the stochastic signal generation element being characterized in that it comprises a processing unit with a first input for receiving said first stochastic signal and a second input for receiving a reference stochastic signal, the latter being generated from a constant value signal and using said random signal, processing them according to at least one arithmetic function, the result whereof is a stochastic output signal representative of said processing. It further consists of a computational neuron that implements said stochastic signal generation element, likewise a neural network that implements said computational neuron.