WaveletPhi[wave,x]
给出符号小波 wave 在 x 处进行计算的尺度函数
.
WaveletPhi[wave]
把尺度函数作为纯函数给出.
WaveletPhi
WaveletPhi[wave,x]
给出符号小波 wave 在 x 处进行计算的尺度函数
.
WaveletPhi[wave]
把尺度函数作为纯函数给出.
更多信息和选项
- 尺度函数
满足递归方程
,其中
是低通滤波器的系数. - WaveletPhi[wave,x,"Dual"] 给出双正交小波诸如 BiorthogonalSplineWavelet 和 ReverseBiorthogonalSplineWavelet 的对偶尺度函数
. - 对偶尺度函数满足递归方程
,其中
是对偶低通滤波器的系数. - 可以使用以下选项:
-
MaxRecursion 8 使用的递归迭代次数 WorkingPrecision MachinePrecision 在内部计算中使用的精度
范例
打开所有单元 关闭所有单元基本范例 (2)
Plot[WaveletPhi[HaarWavelet[], x], {x, -1, 2}, Exclusions -> None]WaveletPhi[HaarWavelet[], x]Plot[WaveletPhi[SymletWavelet[5], x], {x, 0, 9}, PlotRange -> All]WaveletPhi[SymletWavelet[5], x]范围 (4)
ϕ = WaveletPhi[DaubechiesWavelet[3]]Plot[ϕ[x], {x, 0, 5}, PlotRange -> All]Overscript[ϕ, ~] = WaveletPhi[BiorthogonalSplineWavelet[3, 5], x, "Dual"]Plot[Overscript[ϕ, ~], {x, -1, 2}, PlotRange -> All]对于 HaarWavelet 的尺度函数
:
Plot[WaveletPhi[HaarWavelet[], x], {x, -0.5, 1.5}, Exclusions -> None]Plot[WaveletPhi[DaubechiesWavelet[3], x], {x, 0, 5}]Plot[WaveletPhi[SymletWavelet[5], x], {x, 0, 9}, PlotRange -> All]Plot[WaveletPhi[CoifletWavelet[2], x], {x, -4, 7}, PlotRange -> All]Plot[WaveletPhi[BiorthogonalSplineWavelet[2, 4], x], {x, -4, 4}, PlotRange -> All]ReverseBiorthogonalSplineWavelet:
Plot[WaveletPhi[ReverseBiorthogonalSplineWavelet[5, 5], x], {x, -2, 3}, PlotRange -> All]Plot[WaveletPhi[CDFWavelet[], x], {x, -4, 4}, PlotRange -> All]Plot[WaveletPhi[ShannonWavelet[8], x], {x, -8, 8}, PlotRange -> All]Plot[WaveletPhi[BattleLemarieWavelet[6, 8], x], {x, -8, 8}, PlotRange -> All]Plot[Re@WaveletPhi[MeyerWavelet[2, 5], x], {x, -5, 5}, PlotRange -> All]ϕ = WaveletPhi[HaarWavelet[]];
ψ = WaveletPsi[HaarWavelet[]];Table[Plot3D[Evaluate[f[x] g[y]], {x, 0, 1.0}, {y, 0, 1.0}, ExclusionsStyle -> Opacity[0.5], Mesh -> None, Axes -> False], {f, {ϕ, ψ}}, {g, {ϕ, ψ}}]选项 (3)
MaxRecursion (1)
WorkingPrecision (2)
默认情况下,使用 WorkingPrecision->MachinePrecision:
Subscript[ϕ, 1] = WaveletPhi[DaubechiesWavelet[4]]Subscript[ϕ, 2] = WaveletPhi[DaubechiesWavelet[4], WorkingPrecision -> MachinePrecision]Subscript[ϕ, 1] == Subscript[ϕ, 2]WaveletPhi[SymletWavelet[4], 2, WorkingPrecision -> 20]Precision[%]属性和关系 (4)
Integrate[WaveletPhi[HaarWavelet[], x], {x, -∞, ∞}]Table[Integrate[WaveletPhi[HaarWavelet[], (x/2^j)], {x, -∞, ∞}] == 2^j, {j, 0, 4}]ϕ = WaveletPhi[DaubechiesWavelet[2]];a = WaveletFilterCoefficients[DaubechiesWavelet[2], "PrimalLowpass"];scalet[x_, ϕ_, a_] := 2Table[a[[i, 2]]ϕ[2x - a[[i, 1]]], {i, Length[a]}]{Plot[Evaluate@scalet[x, ϕ, a], {x, 0, 3}, PlotRange -> All],
Plot[Total@scalet[x, ϕ, a], {x, 0, 3}, PlotRange -> All]}h[wav_, ω_] := With[{a = WaveletFilterCoefficients[wav]}, Sum[a[[i, 2]]Exp[-I a[[i, 1]]ω], {i, Length[a]}]]Plot[Abs[h[DaubechiesWavelet[2], ω]], {ω, -π, π}, Ticks -> {{-π, -(π/2), 0, (π/2), π}, Automatic}, AxesLabel -> {ω, Abs[H[ω]]}]h[wav_, ω_] := With[{a = WaveletFilterCoefficients[wav]}, Sum[a[[i, 2]]Exp[-I a[[i, 1]]ω], {i, Length[a]}]]fh[wav_, ω_, j_] := Abs[Product[h[wav, (ω/2^i)], {i, j}]]Plot[fh[DaubechiesWavelet[2], ω, 10], {ω, -10Pi, 10Pi}, PlotRange -> All,
AxesLabel -> {ω, Abs[Overscript[ϕ, ^ ][ω]]}]巧妙范例 (1)
ϕ[x_, j_, k_] := 2^j / 2WaveletPhi[CoifletWavelet[1], 2^jx - k]Plot[Evaluate@Table[ϕ[x, j, 0], {j, 0, 4}], {x, -0.5, 0.5}, Filling -> Axis, PlotRange -> All]Plot[Evaluate@Table[ϕ[x, 2, k], {k, 0, 2^2 - 1}], {x, -0.5, 1.5}, Filling -> Axis, PlotRange -> All]文本
Wolfram Research (2010),WaveletPhi,Wolfram 语言函数,https://reference.wolfram.com/language/ref/WaveletPhi.html.
CMS
Wolfram 语言. 2010. "WaveletPhi." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/WaveletPhi.html.
APA
Wolfram 语言. (2010). WaveletPhi. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/WaveletPhi.html 年
BibTeX
@misc{reference.wolfram_2026_waveletphi, author="Wolfram Research", title="{WaveletPhi}", year="2010", howpublished="\url{https://reference.wolfram.com/language/ref/WaveletPhi.html}", note=[Accessed: 14-November-2026]}
BibLaTeX
@online{reference.wolfram_2026_waveletphi, organization={Wolfram Research}, title={WaveletPhi}, year={2010}, url={https://reference.wolfram.com/language/ref/WaveletPhi.html}, note=[Accessed: 14-November-2026]}