ChebyshevU[n,x]
给出了第二类切比雪夫多项式
.
ChebyshevU
ChebyshevU[n,x]
给出了第二类切比雪夫多项式
.
更多信息
- 数学函数,适宜于符号和数值计算.
- 对于整数 n 给出了显式多项式.
. - 对于某些特殊参数,ChebyshevU 自动计算出精确值.
- ChebyshevU 可以计算到任意数值精度.
- ChebyshevU 自动逐项作用于列表的各个元素.
- 对于非整数 n,ChebyshevU[n,z] 在复平面 z 上有分支切割,从
到
. - ChebyshevU 可与 Interval 和 CenteredInterval 对象一起使用. »
范例
打开所有单元 关闭所有单元基本范例 (7)
ChebyshevU[2, 3]计算10次的 ChebyshevU 多项式:
ChebyshevU[10, x]Plot[ChebyshevU[10, x], {x, -1, 1}]ComplexPlot3D[ChebyshevU[5, z], {z, -2 - 2I, 2 + 2I}, PlotLegends -> Automatic]Series[ChebyshevU[5, x], {x, 0, 5}]在 Infinity 处的渐近展开式:
Series[ChebyshevU[1 / 3, x], {x, ∞, 3}]//Normal//FullSimplifySeries[ChebyshevU[1 / 3, x], {x, -1, 2}]//FullSimplify范围 (44)
数值计算 (6)
ChebyshevU[2, 5]ChebyshevU[12, 2.5]N[ChebyshevU[1 / 7, 1 / 3], 50]ChebyshevU[0.3000000000000000000, 0]N[ChebyshevU[98 + I, I]]ChebyshevU[-1.5, -2.4`100]//TimingChebyshevU[84, 63`10000000];//Timing用 Interval 和 CenteredInterval 对象计算最坏情况下的区间:
ChebyshevU[2, Interval[{1.9, 2.1}]]ChebyshevU[2, CenteredInterval[2, 1 / 100]]或用 Around 计算一般情况下的统计区间:
ChebyshevU[2, Around[2, 0.01]]ChebyshevU[2, {{1, 2}, {3, 4}}]或用 MatrixFunction 计算矩阵形式的 ChebyshevU 函数:
MatrixFunction[ChebyshevU[2, #]&, {{1, 2}, {3, 4}}]特殊值 (7)
在固定点的 ChebyshevU 的值:
Table[ChebyshevU[n, Pi / 2], {n, 0, 3}]符号 n 的 ChebyshevU:
ChebyshevU[n, 0]ChebyshevU[0, 0]ChebyshevU[0, Infinity]ChebyshevU[Infinity, 0][[1, 1]]求 ChebyshevU[5,x] 的第一个正极大值:
xmax = x /. Solve[D[ChebyshevU[5, x], x] == 0 && 0 < x < π, x][[1]]Plot[ChebyshevU[5, x], {x, -1, 1}, Epilog -> Style[Point[{xmax, ChebyshevT[5, xmax]}], PointSize[Large], Red]]计算相关的 ChebyshevU[7,x] 多项式:
ChebyshevU[7, x]计算 n 为半整数的 ChebyshevU[1/2,x] 多项式:
ChebyshevU[1 / 2, x]可视化 (3)
绘制各个阶数的 ChebyshevU 函数:
Plot[{ChebyshevU[1, x], ChebyshevU[2, x], ChebyshevU[3, x], ChebyshevU[4, x]}, {x, -1, 1}]ComplexContourPlot[Re[ChebyshevU[3, z]], {z, -3 - 3 I, 3 + 3 I}, IconizedObject[«PlotOptions»]]ComplexContourPlot[Im[ChebyshevU[3, z]], {z, -3 - 3 I, 3 + 3 I}, IconizedObject[«PlotOptions»]]Plot3D[ChebyshevU[n, z], {n, 0, 5}, {z, -1, 1}]函数的属性 (14)
ChebyshevU 对区间 [-1,∞] 内的所有实数有定义:
FunctionDomain[ChebyshevU[n, x], x]ChebyshevU 对除
外的所有复数都有定义:
FunctionDomain[ChebyshevU[n, z], z, Complexes]FunctionRange[ChebyshevU[1, x], x, y]FunctionRange[ChebyshevU[1, z], z, y, Complexes]FunctionRange[ChebyshevU[2, x], x, y]FunctionRange[ChebyshevU[2, z], z, y, Complexes]ChebyshevU[1, -x] == -ChebyshevU[1, x]ChebyshevU[2, -x] == ChebyshevU[2, x]ChebyshevU 逐项作用于列表的各个元素:
ChebyshevU[{1, 2, 3}, x]FunctionAnalytic[ChebyshevU[n, x], x, Assumptions -> n∈ℤ]通常情况下,ChebyshevU 既不是解析函数也不是亚纯函数:
FunctionAnalytic[ChebyshevU[1 / 3, x], x, ℂ]FunctionMeromorphic[ChebyshevU[1 / 3, x], x]FunctionMonotonicity[ChebyshevU[2, x], x]FunctionInjective[ChebyshevU[2, x], x]FunctionInjective[ChebyshevU[1, x], x]Plot[{ChebyshevU[1, x], ChebyshevU[2, x], 2}, {x, -1, 1}]FunctionSurjective[ChebyshevU[2, x], x]FunctionSurjective[ChebyshevU[1, x], x]Plot[{ChebyshevU[1, x], ChebyshevU[2, x], -2}, {x, -1, 1}]FunctionSign[ChebyshevU[2, x], x]FunctionSingularities[ChebyshevU[n, x], x]FunctionDiscontinuities[ChebyshevU[n, x], x]FunctionConvexity[ChebyshevU[2, x], x]TraditionalForm 格式:
ChebyshevU[n, x]//TraditionalForm微分 (3)
D[ChebyshevU[n, x] , x]Table[D[ChebyshevU[n, x], {x, k}], {k, 1, 3}]//SimplifyPlot[Evaluate[% /. n -> 5], {x, -10, 10}, PlotLegends -> {"First Derivative", "Second Derivative", "Third Derivative"}]D[ChebyshevU[n, x], {x, k}]// FullSimplify积分 (4)
使用 Integrate 计算不定积分:
Integrate[ChebyshevU[n, x], x]FullSimplify[D[%, x]]Integrate[ChebyshevU[n, x], {x, 0, 4}]奇整数阶数的 ChebyshevU 在一个周期内的定积分是 0:
Integrate[ChebyshevU[2n - 1, x], {x, -5, 5}]Table[%, {n, 3, 11, 2}]//FullSimplifyIntegrate[ChebyshevU[3, x]ChebyshevT[5, x], x]//FullSimplifyIntegrate[Exp[x] ChebyshevU[5, x], {x, 0, 5}]//FullSimplify级数展开 (3)
使用 Series 求泰勒展开:
Series[ChebyshevU[n, x], {x, 0, 3}]terms = Normal@Table[Series[ChebyshevU[10, x], {x, 0, m}], {m, 1, 5, 2}];
Plot[{ChebyshevU[10, x], terms}, {x, -1, 1}, PlotRange -> {-3, 3}]用 SeriesCoefficient 给出级数展开式的通项:
SeriesCoefficient[ChebyshevU[n, x], {x, 0, n}]Series[ChebyshevU[n, x], {x, x0, 2}]函数恒等式与简化 (4)
ChebyshevU 是通过以下三角恒等式定义的:
ChebyshevU[n, Cos[θ]] == Sin[(n + 1) θ] / Sin[θ]//FullSimplifyChebyshevU 的普通母函数:
Sum[ChebyshevU[n, x]t^n, {n, 0, Infinity}]ChebyshevU 的指数母函数:
Sum[ChebyshevU[n, x]t^n / n!, {n, 0, Infinity}]ChebyshevU[n, z] == 2 z ChebyshevU[n + 1, z] - ChebyshevU[n + 2, z]//FullSimplifyChebyshevU[n - 1, z] + ChebyshevU[n + 1, z] == 2 z ChebyshevU[n, z]//FullSimplify推广和延伸 (2)
可将 ChebyshevU 应用于幂级数:
ChebyshevU[10, Log[1 + x] + O[x] ^ 6]ChebyshevU 可用于 Interval:
ChebyshevU[10, Interval[{-1, 1}]]应用 (7)
coeffs = Table[((2/π)Subsuperscript[∫, -1, 1]Sqrt[1 - x^2] ChebyshevU[n, x] Sinc[2x π]ⅆx), {n, 0, 4}];Plot[{Sinc[2π x], Evaluate[coeffs.Table[ChebyshevU[n, x], {n, 0, 4}]]}, {x, -1, 1}]curve[pts_List] := Function[x, Evaluate[Block[{n = Length[pts]}, pts.Table[ChebyshevU[n - 1, Sin[(k π/n)] Sqrt[1 - x^2] + x Cos[(π k/n)]], {k, 0, n - 1}] / n]]]points[pts_List] := MapIndexed[{-1. Cos[(First[#2]) * Pi / Length[pts]], #1}&, Reverse[pts]]Plot[Evaluate[curve[Range[15]][x]], {x, -1, 1}, Prolog -> {Red, PointSize[0.02], Point[points[Range[15]]]}]Plot[ Evaluate[Table[1 / (1 + k^2 ChebyshevU[n, Cos[k] + Sinc[k]]^2), {n, 0, 5}]], {k, 0, 10}, PlotRange -> All]toeplitzTridiagonal[a_, b_, c_, n_] := SparseArray[{Band[{2, 1}] -> a, Band[{1, 1}] -> b, Band[{1, 2}] -> c}, {n, n}]toeplitzTridiagonal[a, b, c, 4]//MatrixFormToeplitz 三对角矩阵的特征多项式可以用 ChebyshevU 来表示:
cPoly[a_, b_, c_, n_, x_] := (-Sqrt[a c])^n ChebyshevU[n, (x - b/2Sqrt[a c])]Table[CharacteristicPolynomial[toeplitzTridiagonal[a, b, c, n], x] == cPoly[a, b, c, n, x]//Simplify, {n, 2, 9}]定义 Kac–Murdock–Szegő (KMS) 矩阵,它是一个对称的托普利兹矩阵:
kms[ρ_, n_] := ToeplitzMatrix[ρ^Range[0, n - 1]]KMS 矩阵是一阶自回归过程(即 AR(1) 过程)的相关矩阵:
n = 6;
kms[ρ, n] == Correlation[ARProcess[{ρ}, σ ^ 2][Range[n]]]//SimplifyKMS 矩阵的特征多项式可以用 ChebyshevU 表示:
CharacteristicPolynomial[kms[ρ, n], λ] == With[{τ = (ρ^2(λ + 1) + λ - 1/2ρ λ)}, ((ρ λ)^n/1 - ρ^2)(ChebyshevU[n, τ] - 2ρ ChebyshevU[n - 1, τ] + ρ^2ChebyshevU[n - 2, τ])]//Simplify用 ChebyshevU 函数作为非齐次部分,解微分方程:
DSolve[y''[x] + ChebyshevU[n, x] == 0, y[x], x]Series[1 / (1 - 2 t x + t ^ 2), {t, 0, 4}]SeriesCoefficient[%, 4]ChebyshevU[4, x]属性和关系 (7)
给出 ChebyshevU 多项式中的系数列表:
CoefficientList[ ChebyshevU[10, x], x]利用 FunctionExpand 展开三角函数:
FunctionExpand[ChebyshevU[n, x]]ChebyshevU 相对于
的导数:
D[ChebyshevU[n, x], x]可以用 DifferenceRoot 来表示ChebyshevU:
DifferenceRootReduce[ChebyshevU[k, z], k]ChebyshevU 级数展开式中的一般项:
SeriesCoefficient[ChebyshevU[a, x], {x, 0, n}]ChebyshevU 的母函数:
GeneratingFunction[ChebyshevU[n, k], n, x]ChebyshevU 的指数母函数:
ExponentialGeneratingFunction[ChebyshevU[n, k], n, x]技术笔记
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- 正交多项式
相关指南
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- 特殊函数
历史
1988年引入 (1.0) | 在以下年份被更新:2021 (13.0) ▪ 2022 (13.1)
文本
Wolfram Research (1988),ChebyshevU,Wolfram 语言函数,https://reference.wolfram.com/language/ref/ChebyshevU.html (更新于 2022 年).
CMS
Wolfram 语言. 1988. "ChebyshevU." Wolfram 语言与系统参考资料中心. Wolfram Research. 最新版本 2022. https://reference.wolfram.com/language/ref/ChebyshevU.html.
APA
Wolfram 语言. (1988). ChebyshevU. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/ChebyshevU.html 年
BibTeX
@misc{reference.wolfram_2026_chebyshevu, author="Wolfram Research", title="{ChebyshevU}", year="2022", howpublished="\url{https://reference.wolfram.com/language/ref/ChebyshevU.html}", note=[Accessed: 09-August-2026]}
BibLaTeX
@online{reference.wolfram_2026_chebyshevu, organization={Wolfram Research}, title={ChebyshevU}, year={2022}, url={https://reference.wolfram.com/language/ref/ChebyshevU.html}, note=[Accessed: 09-August-2026]}