کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
404375 677417 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multivariate sigmoidal neural network approximation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Multivariate sigmoidal neural network approximation
چکیده انگلیسی

Here we study the multivariate quantitative constructive approximation of real and complex valued continuous multivariate functions on a box or RNRN, N∈NN∈N, by the multivariate quasi-interpolation sigmoidal neural network operators. The “right” operators for our goal are fully and precisely described. This approximation is derived by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high order partial derivatives. Our multivariate operators are defined by using a multidimensional density function induced by the logarithmic sigmoidal function. The approximations are pointwise and uniform. The related feed-forward neural network is with one hidden layer.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neural Networks - Volume 24, Issue 4, May 2011, Pages 378–386
نویسندگان
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