<p>It is known that, in general, an affine or Gabor AP-frame is an <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(L^2(\mathbb {R})\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mi>L</mi> <mn>2</mn> </msup> <mrow> <mo stretchy="false">(</mo> <mi mathvariant="double-struck">R</mi> <mo stretchy="false">)</mo> </mrow> </mrow> </math></EquationSource> </InlineEquation>-frame and conversely. In part as a consequence of the Ergodic Theorem, we prove a necessary and sufficient condition for an affine (wavelet) system <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\mathcal {A}=\{a^{j/2} \psi _{j,k}(t):=a^{-j/2} \psi (a^{-j} t -k):j\in \mathbb {Z}, k\in \mathbb {K}:=b\mathbb {Z}\}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="script">A</mi> <mo>=</mo> <mo stretchy="false">{</mo> <msup> <mi>a</mi> <mrow> <mi>j</mi> <mo stretchy="false">/</mo> <mn>2</mn> </mrow> </msup> <msub> <mi>ψ</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mrow> <mo stretchy="false">(</mo> <mi>t</mi> <mo stretchy="false">)</mo> </mrow> <mo>:</mo> <mo>=</mo> <msup> <mi>a</mi> <mrow> <mo>-</mo> <mi>j</mi> <mo stretchy="false">/</mo> <mn>2</mn> </mrow> </msup> <mi>ψ</mi> <mrow> <mo stretchy="false">(</mo> <msup> <mi>a</mi> <mrow> <mo>-</mo> <mi>j</mi> </mrow> </msup> <mi>t</mi> <mo>-</mo> <mi>k</mi> <mo stretchy="false">)</mo> </mrow> <mo>:</mo> <mi>j</mi> <mo>∈</mo> <mi mathvariant="double-struck">Z</mi> <mo>,</mo> <mi>k</mi> <mo>∈</mo> <mi mathvariant="double-struck">K</mi> <mo>:</mo> <mo>=</mo> <mi>b</mi> <mi mathvariant="double-struck">Z</mi> <mo stretchy="false">}</mo> </mrow> </math></EquationSource> </InlineEquation> to be an affine AP-Frame in terms of Gaussian stationary random processes expanding in this way what we have done recently for Gabor systems. Likewise, we study a connection between the decay of the associated stationary sequences <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\{\langle {X,\psi _{j,k}}\rangle : k\in \mathbb {K}\}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo stretchy="false">{</mo> <mrow> <mo stretchy="false">⟨</mo> <mrow> <mi>X</mi> <mo>,</mo> <msub> <mi>ψ</mi> <mrow> <mi>j</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> </mrow> <mo stretchy="false">⟩</mo> </mrow> <mo>:</mo> <mi>k</mi> <mo>∈</mo> <mi mathvariant="double-struck">K</mi> <mo stretchy="false">}</mo> </mrow> </math></EquationSource> </InlineEquation> for each <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(j\in \mathbb {Z}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>j</mi> <mo>∈</mo> <mi mathvariant="double-struck">Z</mi> </mrow> </math></EquationSource> </InlineEquation>, and a smoothness condition on a Gaussian stationary random process <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(X=(X(t))_{t\in \mathbb {R}}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>X</mi> <mo>=</mo> <msub> <mrow> <mo stretchy="false">(</mo> <mi>X</mi> <mrow> <mo stretchy="false">(</mo> <mi>t</mi> <mo stretchy="false">)</mo> </mrow> <mo stretchy="false">)</mo> </mrow> <mrow> <mi>t</mi> <mo>∈</mo> <mi mathvariant="double-struck">R</mi> </mrow> </msub> </mrow> </math></EquationSource> </InlineEquation>.</p>

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Affine AP-frames and stationary random processes

  • Hernán D. Centeno,
  • Juan M. Medina

摘要

It is known that, in general, an affine or Gabor AP-frame is an \(L^2(\mathbb {R})\) L 2 ( R ) -frame and conversely. In part as a consequence of the Ergodic Theorem, we prove a necessary and sufficient condition for an affine (wavelet) system \(\mathcal {A}=\{a^{j/2} \psi _{j,k}(t):=a^{-j/2} \psi (a^{-j} t -k):j\in \mathbb {Z}, k\in \mathbb {K}:=b\mathbb {Z}\}\) A = { a j / 2 ψ j , k ( t ) : = a - j / 2 ψ ( a - j t - k ) : j Z , k K : = b Z } to be an affine AP-Frame in terms of Gaussian stationary random processes expanding in this way what we have done recently for Gabor systems. Likewise, we study a connection between the decay of the associated stationary sequences \(\{\langle {X,\psi _{j,k}}\rangle : k\in \mathbb {K}\}\) { X , ψ j , k : k K } for each \(j\in \mathbb {Z}\) j Z , and a smoothness condition on a Gaussian stationary random process \(X=(X(t))_{t\in \mathbb {R}}\) X = ( X ( t ) ) t R .