31 resultados para Variational approximation
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2000 Mathematics Subject Classification: 26A33 (primary), 35S15 (secondary)
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2000 Mathematics Subject Classification: 26A33 (primary), 35S15
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The paper presents an example of methodological approach to the development of variational thinking skills in teaching programming. Various ways in solving a given task are implemented for the purpose. One of the forms, through which the variational thinking is manifested, is related to trail practical actions. In the process of comprehension of the properties thus acquired, students are doing their own (correct or incorrect) conclusions for other, hidden properties and at the same time they discover possibilities for new ways of action and acquiring of new effects. The variability and the generalizing function of thinking are in a close interrelation, and their interaction to a great extend determines the dynamics of the cognitive activity of the student.
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2000 Mathematics Subject Classification: 47H04, 65K10.
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2000 Mathematics Subject Classification: 46B03
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2000 Mathematics Subject Classification: 49J40, 49J35, 58E30, 47H05
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2010 Mathematics Subject Classification: 41A25, 41A10.
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ACM Computing Classification System (1998): G.1.2.
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The deviations of some entire functions of exponential type from real-valued functions and their derivatives are estimated. As approximation metrics we use the Lp-norms and power variations on R. Theorems presented here correspond to the Ganelius and Popov results concerning the one-sided trigonometric approximation of periodic functions (see [4, 5 and 8]). Some related facts were announced in [2, 3, 6 and 7].
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We introduce a modification of the familiar cut function by replacing the linear part in its definition by a polynomial of degree p + 1 obtaining thus a sigmoid function called generalized cut function of degree p + 1 (GCFP). We then study the uniform approximation of the (GCFP) by smooth sigmoid functions such as the logistic and the shifted logistic functions. The limiting case of the interval-valued Heaviside step function is also discussed which imposes the use of Hausdorff metric. Numerical examples are presented using CAS MATHEMATICA.
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AMS Subject Classification 2010: 41A25, 41A35, 41A40, 41A63, 41A65, 42A38, 42A85, 42B10, 42B20
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MSC 2010: 41A25, 41A35
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2000 Mathematics Subject Classification: 26E25, 41A35, 41A36, 47H04, 54C65.
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2000 Mathematics Subject Classification: 34L40, 65L10, 65Z05, 81Q20.
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AMS classification: 41A36, 41A10, 41A25, 41Al7.