polyint
Polynomial integration
Description
Examples
Integrate Quartic Polynomial
Evaluate the definite integral
Create a vector to represent the polynomial integrand . The term is absent and thus has a coefficient of 0.
p = [3 0 -4 10 -25];
Use polyint
to integrate the polynomial using a constant of integration equal to 0
.
q = polyint(p)
q = 1×6
0.6000 0 -1.3333 5.0000 -25.0000 0
Find the value of the integral by evaluating q
at the limits of integration.
a = -1; b = 3; I = diff(polyval(q,[a b]))
I = 49.0667
Integrate Product of Two Polynomials
Evaluate
Create vectors to represent the polynomials and .
p = [1 0 -1 0 0 1]; v = [1 0 1];
Multiply the polynomials and integrate the resulting expression using a constant of integration k = 3
.
k = 3; q = polyint(conv(p,v),k)
q = 1×9
0.1250 0 0 0 -0.2500 0.3333 0 1.0000 3.0000
Find the value of I
by evaluating q
at the limits of integration.
a = 0; b = 2; I = diff(polyval(q,[a b]))
I = 32.6667
Input Arguments
p
— Polynomial coefficients
vector
Polynomial coefficients, specified as a vector. For example,
the vector [1 0 1]
represents the polynomial ,
and the vector [3.13 -2.21 5.99]
represents the
polynomial .
For more information, see Create and Evaluate Polynomials.
Data Types: single
| double
Complex Number Support: Yes
k
— Constant of integration
numeric scalar
Constant of integration, specified as a numeric scalar.
Example: polyint([1 0 0],3)
Data Types: single
| double
Complex Number Support: Yes
Output Arguments
q
— Integrated polynomial coefficients
row vector
Integrated polynomial coefficients, returned as a row vector. For more information, see Create and Evaluate Polynomials.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
Thread-Based Environment
Run code in the background using MATLAB® backgroundPool
or accelerate code with Parallel Computing Toolbox™ ThreadPool
.
This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
The polyint
function
fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray
(Parallel Computing Toolbox). For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced before R2006a
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