Conditional Fourier-Feynman transforms and convolutions of unbounded functions on a generalized Wiener space (Q2861458)
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scientific article; zbMATH DE number 6224170
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Conditional Fourier-Feynman transforms and convolutions of unbounded functions on a generalized Wiener space |
scientific article; zbMATH DE number 6224170 |
Statements
8 November 2013
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analogue of Wiener space
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analytic conditional Feynman integral
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analytic conditional Fourier-Feynman transform
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analytic conditional Wiener integral
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conditional convolution product
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Wiener space
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Conditional Fourier-Feynman transforms and convolutions of unbounded functions on a generalized Wiener space (English)
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The author summarizes the content of this paper in the following abstract: Let \(C[0,t]\) denote the function space of real-valued continuous paths on \([0,t]\). Define \(X_n:C[0,t]\to \mathbb R^{n+1}\) and \(X_{n+1}:C[0,t]\to \mathbb R^{n+2}\) by \(X_n(x)=(x(t_0),x(t_1),\dots,x(t_n))\) and \(X_{n+1}(x)=(x(t_0),x(t_1),\dots,x(t_n),x(t_{n+1}))\), respectively, where \(0=t_0 < t_1 < \dots < t_n < t_{n+1}= t\). In the present paper, using simple formulas for the conditional expectations with the conditioning functions \(X_n\) and \(X_{n+1}\), we evaluate the \(L_p\) \((1\leq p\leq \infty)\)-analytic conditional Fourier-Feynman transforms and the conditional convolution products of the functions, which have the form \(f_r((v_1,x),\dots,(v_r,x))\int_{L_2[0,t]}\exp\{i(v,x)\}\text{d}\sigma(v)\) for \(x\in C[0,t]\), where \(\{v_1,\dots,v_r\}\) is an orthonormal subset of \(L_2[0,t]\), \(f_r\in L_p(\mathbb R^r)\), and \(\sigma\) is the complex Borel measure of bounded variation on \(L_2[0,t]\). We then investigate the inverse conditional Fourier-Feynman transforms of the function and prove that the analytic conditional Fourier-Feynman transforms of the conditional convolution products for the functions can be expressed by the products of the analytic conditional Fourier-Feynman transform of each function.
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0.9189971089363098
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0.8877955675125122
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