"sigmoid function" meaning in English

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        {
          "text": "1995, Jun Han, Claudio Moraga, The Influence of the Sigmoid Function Parameters on the Speed of Backpropagation Learning, José Mira, Francisco Sandoval (editors), From Natural to Artificial Neural Computation: International Workshop on Artificial Neural Networks, Proceedings, Springer, LNCS 930, page 195,\n[The] [s]igmoid function is the most commonly known function used in feed forward neural networks because of its nonlinearity and the computational simplicity of its derivative."
        },
        {
          "ref": "2012, Walter Freeman, Neurodynamics: An Exploration in Mesoscopic Brain Dynamics, Springer, page 241:",
          "text": "The first significant new insight from gamma spatial analysis emerged on re-examination of the sigmoid function representing bilateral saturation.",
          "type": "quote"
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          "text": "2016, Roumen Anguelov, Svetoslav Markov, Hausdorff Continuous Interval Functions and Applications, Marco Nehmeier, Jürgen Wolff von Gudenberg, Warwick Tucker (editors), Scientific Computing, Computer Arithmetic, and Validated Numerics: 16th International Symposium, SCAN 2014, Springer, LNCS 9553, page 10,\nSigmoid functions find multiple applications to neural networks and cell growth population models [14,20]. A sigmoid function on R with a range [a,b] is defined as a monotone function s(t): R →[a,b] such that lim _(t→-∞)s(t)=a, and lim _(t→∞)s(t)=b."
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        "Any of various real functions whose graph resembles an elongated letter \"S\"; specifically, the logistic function y=(eˣ)/(eˣ+1)=1/(1+e⁻ˣ)."
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        "(mathematical analysis, statistics) Any of various real functions whose graph resembles an elongated letter \"S\"; specifically, the logistic function y=(eˣ)/(eˣ+1)=1/(1+e⁻ˣ)."
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          "sense": "\"S\"-shaped function",
          "word": "sigmoid"
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            "feminine"
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          "word": "Sigmoidfunktion"
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          "text": "1995, Jun Han, Claudio Moraga, The Influence of the Sigmoid Function Parameters on the Speed of Backpropagation Learning, José Mira, Francisco Sandoval (editors), From Natural to Artificial Neural Computation: International Workshop on Artificial Neural Networks, Proceedings, Springer, LNCS 930, page 195,\n[The] [s]igmoid function is the most commonly known function used in feed forward neural networks because of its nonlinearity and the computational simplicity of its derivative."
        },
        {
          "ref": "2012, Walter Freeman, Neurodynamics: An Exploration in Mesoscopic Brain Dynamics, Springer, page 241:",
          "text": "The first significant new insight from gamma spatial analysis emerged on re-examination of the sigmoid function representing bilateral saturation.",
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        },
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          "text": "2016, Roumen Anguelov, Svetoslav Markov, Hausdorff Continuous Interval Functions and Applications, Marco Nehmeier, Jürgen Wolff von Gudenberg, Warwick Tucker (editors), Scientific Computing, Computer Arithmetic, and Validated Numerics: 16th International Symposium, SCAN 2014, Springer, LNCS 9553, page 10,\nSigmoid functions find multiple applications to neural networks and cell growth population models [14,20]. A sigmoid function on R with a range [a,b] is defined as a monotone function s(t): R →[a,b] such that lim _(t→-∞)s(t)=a, and lim _(t→∞)s(t)=b."
        }
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      "word": "Sigmoidfunktion"
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