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Construction of stationary self-similar generalized fields by random wavelet expansion. (English) Zbl 1008.60055
The wavelet expansion operator $$\Psi_{g,H}$$ with mother wavelet $$g$$ of index $$H$$ is defined by $(\Psi_{g,H}\varphi)(u,v)= \int_{\mathbb R^n} e^{Hu}g(e^ux+v)\varphi(x) dx,\quad \varphi\in{\mathcal S}_k(\mathbb R^n).$ Let $$W=\sum_{i}\delta(u-u_i)\delta(v-v_i)$$ and define the random image $$I = {\Psi_{g,H}}^* W$$, where $$(u_i, v_i)$$ means the location and $$H$$ the distance of $$i$$th figure. For the scaling operator $$S_t\varphi(x)=t^{-n}\varphi(t^{-1}x)$$ and the translation operator $$T_v\varphi(x)=\varphi(x-v)$$, it holds $(\Psi_{g,H}T_{v_0}S_{e^{u_0}}\varphi)(u,v)= e^{-Hu_0}(U_{u_0,v_0}\Psi_{g,H}\varphi)(u,v),$ where $$(U_{u_0,v_0}f)(u,v)=f(u+u_0, v+e^u v_0).$$ Three types of stationary self-similar random fields are constructed as the above “random images” with randomly located figures: (1) a multiple-stochastic integral over the products domain of scale and translate, (2) an iterated one over the scale domain, (3) an iterated one over the translate domain.

##### MSC:
 60G18 Self-similar stochastic processes
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