-
函数
- AbsoluteCorrelation
- Adjugate
- ArgMax
- ArgMin
- ArrayDot
- ArrayExpand
- Arrays
- ArraySimplify
- ArraySymbol
- AsymptoticDSolveValue
- AsymptoticRSolveValue
- CentralMoment
- ComponentExpand
- ConicOptimization
- ConvexOptimization
- Correlation
- Covariance
- Cross
- Cumulant
- D
- Det
- Div
- Dot
- DSolve
- DSolveValue
- Equal
- FactorialMoment
- FindArgMax
- FindArgMin
- FindInstance
- FindMaximum
- FindMaxValue
- FindMinimum
- FindMinValue
- FindRoot
- GeometricOptimization
- Grad
- Integrate
- Inverse
- KroneckerProduct
- Kurtosis
- Laplacian
- LeastSquares
- Limit
- LinearFractionalOptimization
- LinearOptimization
- LinearSolve
- LineIntegrate
- Matrices
- MatrixExp
- MatrixFunction
- MatrixLog
- MatrixPower
- MatrixSymbol
- Maximize
- MaxLimit
- MaxValue
- Mean
- Minimize
- MinLimit
- MinValue
- Moment
- NArgMax
- NArgMin
- NDSolve
- NDSolveValue
- NIntegrate
- NLineIntegrate
- NMaximize
- NMaxValue
- NMinimize
- NMinValue
- NonThreadable
- Norm
- NSolve
- NSolveValues
- NSurfaceIntegrate
- ParametricConvexOptimization
- ParametricNDSolveValue
- PseudoInverse
- QuadraticOptimization
- Reduce
- RobustConvexOptimization
- RSolve
- RSolveValue
- SecondOrderConeOptimization
- SemidefiniteOptimization
- Skewness
- Solve
- SolveValues
- StandardDeviation
- SurfaceIntegrate
- SymbolicDeltaProductArray
- SymbolicIdentityArray
- SymbolicOnesArray
- SymbolicZerosArray
- TensorContract
- TensorProduct
- TensorWedge
- Total
- Tr
- Transpose
- Unequal
- Variance
- VectorGreater
- VectorGreaterEqual
- VectorLess
- VectorLessEqual
- Vectors
- VectorSymbol
- 相关指南
-
-
函数
- AbsoluteCorrelation
- Adjugate
- ArgMax
- ArgMin
- ArrayDot
- ArrayExpand
- Arrays
- ArraySimplify
- ArraySymbol
- AsymptoticDSolveValue
- AsymptoticRSolveValue
- CentralMoment
- ComponentExpand
- ConicOptimization
- ConvexOptimization
- Correlation
- Covariance
- Cross
- Cumulant
- D
- Det
- Div
- Dot
- DSolve
- DSolveValue
- Equal
- FactorialMoment
- FindArgMax
- FindArgMin
- FindInstance
- FindMaximum
- FindMaxValue
- FindMinimum
- FindMinValue
- FindRoot
- GeometricOptimization
- Grad
- Integrate
- Inverse
- KroneckerProduct
- Kurtosis
- Laplacian
- LeastSquares
- Limit
- LinearFractionalOptimization
- LinearOptimization
- LinearSolve
- LineIntegrate
- Matrices
- MatrixExp
- MatrixFunction
- MatrixLog
- MatrixPower
- MatrixSymbol
- Maximize
- MaxLimit
- MaxValue
- Mean
- Minimize
- MinLimit
- MinValue
- Moment
- NArgMax
- NArgMin
- NDSolve
- NDSolveValue
- NIntegrate
- NLineIntegrate
- NMaximize
- NMaxValue
- NMinimize
- NMinValue
- NonThreadable
- Norm
- NSolve
- NSolveValues
- NSurfaceIntegrate
- ParametricConvexOptimization
- ParametricNDSolveValue
- PseudoInverse
- QuadraticOptimization
- Reduce
- RobustConvexOptimization
- RSolve
- RSolveValue
- SecondOrderConeOptimization
- SemidefiniteOptimization
- Skewness
- Solve
- SolveValues
- StandardDeviation
- SurfaceIntegrate
- SymbolicDeltaProductArray
- SymbolicIdentityArray
- SymbolicOnesArray
- SymbolicZerosArray
- TensorContract
- TensorProduct
- TensorWedge
- Total
- Tr
- Transpose
- Unequal
- Variance
- VectorGreater
- VectorGreaterEqual
- VectorLess
- VectorLessEqual
- Vectors
- VectorSymbol
- 相关指南
-
函数
符号向量、矩阵和数组
通过使用符号来表示向量、矩阵或数组,人们可以获得一种有效的符号来模拟数学问题. 事实上,大多数科学、工程和统计领域都已转向使用这种更抽象、更高效的符号. Wolfram 语言具有丰富的符号数组语言来描述问题. 大多数高级求解器都支持符号数组表达式和数组变量,从而可以轻松高效地指定高维问题.
符号数组变量
x∈Vectors[…] — 假设 x 是一个矢量
VectorSymbol — 定义一个可以与可列出函数一起使用的矢量符号
MatrixSymbol ▪ ArraySymbol ▪ NonThreadable
符号数组常数
SymbolicZerosArray ▪ SymbolicOnesArray ▪ SymbolicIdentityArray ▪ SymbolicDeltaProductArray
符号数组函数
Dot — 向量与矩阵的内积
ArrayDot — 广义数组内积
Norm ▪ Tr ▪ Det ▪ Cross ▪ Transpose ▪ TensorProduct ▪ TensorContract ▪ KroneckerProduct ▪ TensorWedge
Inverse ▪ Adjugate ▪ PseudoInverse ▪ LinearSolve ▪ LeastSquares ▪ MatrixPower ▪ MatrixExp ▪ MatrixLog ▪ MatrixFunction
Total ▪ Mean ▪ StandardDeviation ▪ Variance ▪ Covariance ▪ Correlation ▪ AbsoluteCorrelation ▪ Kurtosis ▪ Skewness ▪ Moment ▪ CentralMoment ▪ FactorialMoment ▪ Cumulant
符号数组谓词
VectorLessEqual ▪ VectorLess ▪ VectorGreaterEqual ▪ VectorGreater
化简与变换
ArraySimplify — 化简符号数组表达式
ArrayExpand — 展开符号数组表达式
ComponentExpand — 将符号数组表达式展开为用其组成元素表示的表达式
数组导数
D — 相对于向量、矩阵和数组变量的符号微分
数组的极限
Limit — 用符号向量变量计算极限
数组代数等式求解器
Solve — 求解含有符号数组变量的方程和不等式
NSolve ▪ SolveValues ▪ NSolveValues ▪ Reduce ▪ FindInstance ▪ FindRoot
数组优化求解器
Minimize — 用符号数组变量进行优化
MinValue ▪ ArgMin ▪ Maximize ▪ MaxValue ▪ ArgMax ▪ NMinimize ▪ NMinValue ▪ NArgMin ▪ NMaximize ▪ NMaxValue ▪ NArgMax ▪ FindMinimum ▪ FindMinValue ▪ FindArgMin ▪ FindMaximum ▪ FindMaxValue ▪ FindArgMax
ConvexOptimization ▪ ParametricConvexOptimization ▪ RobustConvexOptimization ▪ LinearOptimization ▪ LinearFractionalOptimization ▪ QuadraticOptimization ▪ SecondOrderConeOptimization ▪ SemidefiniteOptimization ▪ GeometricOptimization ▪ ConicOptimization
数组积分求解器
Integrate, NIntegrate — 对含有符号向量变量的表达式进行积分
LineIntegrate ▪ NLineIntegrate ▪ SurfaceIntegrate ▪ NSurfaceIntegrate
数组微分方程求解器
NDSolve — 求解含有符号数组变量的微分方程
DSolve ▪ NDSolveValue ▪ DSolveValue ▪ ParametricNDSolveValue ▪ AsymptoticDSolveValue
数组差分方程求解器
RSolve — 求解含有符号数组变量的差分方程