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JKalman | |||||||||
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Packages that use Matrix | |
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jama | |
jkalman | JKalman - Java Kalman Filter main package. |
Uses of Matrix in jama |
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Methods in jama that return Matrix | |
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Matrix |
Matrix.arrayLeftDivide(Matrix B)
Element-by-element left division, C = A. |
Matrix |
Matrix.arrayLeftDivideEquals(Matrix B)
Element-by-element left division in place, A = A. |
Matrix |
Matrix.arrayRightDivide(Matrix B)
Element-by-element right division, C = A. |
Matrix |
Matrix.arrayRightDivideEquals(Matrix B)
Element-by-element right division in place, A = A. |
Matrix |
Matrix.arrayTimes(Matrix B)
Element-by-element multiplication, C = A. |
Matrix |
Matrix.arrayTimesEquals(Matrix B)
Element-by-element multiplication in place, A = A. |
static Matrix |
Matrix.constructWithCopy(double[][] A)
Construct a matrix from a copy of a 2-D array. |
Matrix |
Matrix.copy()
Make a deep copy of a matrix |
Matrix |
Matrix.gemm(Matrix B,
Matrix C,
double alpha,
double beta)
Generalized linear algebraic matrix-matrix multiplication (of A); C = alpha*A x B + beta*C. |
Matrix |
EigenvalueDecomposition.getD()
Return the block diagonal eigenvalue matrix |
Matrix |
QRDecomposition.getH()
Return the Householder vectors |
Matrix |
CholeskyDecomposition.getL()
Return triangular factor. |
Matrix |
LUDecomposition.getL()
Return lower triangular factor |
Matrix |
Matrix.getMatrix(int[] r,
int[] c)
Get a submatrix. |
Matrix |
Matrix.getMatrix(int[] r,
int j0,
int j1)
Get a submatrix. |
Matrix |
Matrix.getMatrix(int i0,
int i1,
int[] c)
Get a submatrix. |
Matrix |
Matrix.getMatrix(int i0,
int i1,
int j0,
int j1)
Get a submatrix. |
Matrix |
QRDecomposition.getQ()
Generate and return the (economy-sized) orthogonal factor |
Matrix |
QRDecomposition.getR()
Return the upper triangular factor |
Matrix |
SingularValueDecomposition.getS()
Return the diagonal matrix of singular values |
Matrix |
LUDecomposition.getU()
Return upper triangular factor |
Matrix |
SingularValueDecomposition.getU()
Return the left singular vectors |
Matrix |
EigenvalueDecomposition.getV()
Return the eigenvector matrix |
Matrix |
SingularValueDecomposition.getV()
Return the right singular vectors |
Matrix |
Matrix.identity()
Generate identity matrix |
static Matrix |
Matrix.identity(int m,
int n)
Generate identity matrix |
static Matrix |
Matrix.identity(int m,
int n,
double value)
Generate identity matrix |
Matrix |
Matrix.inverse()
Matrix inverse or pseudoinverse |
Matrix |
Matrix.minus(Matrix B)
C = A - B |
Matrix |
Matrix.minusEquals(Matrix B)
A = A - B |
Matrix |
Matrix.plus(Matrix B)
C = A + B |
Matrix |
Matrix.plusEquals(Matrix B)
A = A + B |
static Matrix |
Matrix.random(int m,
int n)
Generate matrix with random elements |
static Matrix |
Matrix.read(java.io.BufferedReader input)
Read a matrix from a stream. |
Matrix |
CholeskyDecomposition.solve(Matrix B)
Solve A*X = B |
Matrix |
LUDecomposition.solve(Matrix B)
Solve A*X = B |
Matrix |
Matrix.solve(Matrix B)
Solve A*X = B |
Matrix |
QRDecomposition.solve(Matrix B)
Least squares solution of A*X = B |
Matrix |
Matrix.solveTranspose(Matrix B)
Solve X*A = B, which is also A'*X' = B' |
Matrix |
Matrix.times(double s)
Multiply a matrix by a scalar, C = s*A |
Matrix |
Matrix.times(Matrix B)
Linear algebraic matrix multiplication, A * B |
Matrix |
Matrix.timesEquals(double s)
Multiply a matrix by a scalar in place, A = s*A |
Matrix |
Matrix.transpose()
Matrix transpose. |
Matrix |
Matrix.uminus()
Unary minus |
Methods in jama with parameters of type Matrix | |
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Matrix |
Matrix.arrayLeftDivide(Matrix B)
Element-by-element left division, C = A. |
Matrix |
Matrix.arrayLeftDivideEquals(Matrix B)
Element-by-element left division in place, A = A. |
Matrix |
Matrix.arrayRightDivide(Matrix B)
Element-by-element right division, C = A. |
Matrix |
Matrix.arrayRightDivideEquals(Matrix B)
Element-by-element right division in place, A = A. |
Matrix |
Matrix.arrayTimes(Matrix B)
Element-by-element multiplication, C = A. |
Matrix |
Matrix.arrayTimesEquals(Matrix B)
Element-by-element multiplication in place, A = A. |
Matrix |
Matrix.gemm(Matrix B,
Matrix C,
double alpha,
double beta)
Generalized linear algebraic matrix-matrix multiplication (of A); C = alpha*A x B + beta*C. |
Matrix |
Matrix.minus(Matrix B)
C = A - B |
Matrix |
Matrix.minusEquals(Matrix B)
A = A - B |
Matrix |
Matrix.plus(Matrix B)
C = A + B |
Matrix |
Matrix.plusEquals(Matrix B)
A = A + B |
void |
Matrix.setMatrix(int[] r,
int[] c,
Matrix X)
Set a submatrix. |
void |
Matrix.setMatrix(int[] r,
int j0,
int j1,
Matrix X)
Set a submatrix. |
void |
Matrix.setMatrix(int i0,
int i1,
int[] c,
Matrix X)
Set a submatrix. |
void |
Matrix.setMatrix(int i0,
int i1,
int j0,
int j1,
Matrix X)
Set a submatrix. |
Matrix |
CholeskyDecomposition.solve(Matrix B)
Solve A*X = B |
Matrix |
LUDecomposition.solve(Matrix B)
Solve A*X = B |
Matrix |
Matrix.solve(Matrix B)
Solve A*X = B |
Matrix |
QRDecomposition.solve(Matrix B)
Least squares solution of A*X = B |
Matrix |
Matrix.solveTranspose(Matrix B)
Solve X*A = B, which is also A'*X' = B' |
Matrix |
Matrix.times(Matrix B)
Linear algebraic matrix multiplication, A * B |
Constructors in jama with parameters of type Matrix | |
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EigenvalueDecomposition(Matrix Arg)
Check for symmetry, then construct the eigenvalue decomposition |
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CholeskyDecomposition(Matrix Arg)
Cholesky algorithm for symmetric and positive definite matrix. |
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LUDecomposition(Matrix A)
LU Decomposition |
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QRDecomposition(Matrix A)
QR Decomposition, computed by Householder reflections. |
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SingularValueDecomposition(Matrix Arg)
Construct the singular value decomposition |
Uses of Matrix in jkalman |
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Methods in jkalman that return Matrix | |
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Matrix |
JKalman.Correct(Matrix measurement)
Adjusts model state. |
Matrix |
JKalman.getControl_matrix()
Getter |
Matrix |
JKalman.getError_cov_post()
Getter |
Matrix |
JKalman.getError_cov_pre()
Getter |
Matrix |
JKalman.getGain()
Getter |
Matrix |
JKalman.getMeasurement_matrix()
Getter |
Matrix |
JKalman.getMeasurement_noise_cov()
Getter |
Matrix |
JKalman.getProcess_noise_cov()
Getter |
Matrix |
JKalman.getState_post()
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Matrix |
JKalman.getState_pre()
Getter |
Matrix |
JKalman.getTransition_matrix()
|
Matrix |
JKalman.Predict()
Alias for prediction with no control. |
Matrix |
JKalman.Predict(Matrix control)
Estimates subsequent model state. |
Methods in jkalman with parameters of type Matrix | |
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Matrix |
JKalman.Correct(Matrix measurement)
Adjusts model state. |
Matrix |
JKalman.Predict(Matrix control)
Estimates subsequent model state. |
void |
JKalman.setControl_matrix(Matrix control_matrix)
Setter |
void |
JKalman.setError_cov_post(Matrix error_cov_post)
Setter |
void |
JKalman.setError_cov_pre(Matrix error_cov_pre)
Setter |
void |
JKalman.setGain(Matrix gain)
Setter |
void |
JKalman.setMeasurement_matrix(Matrix measurement_matrix)
Setter |
void |
JKalman.setMeasurement_noise_cov(Matrix measurement_noise_cov)
Setter |
void |
JKalman.setProcess_noise_cov(Matrix process_noise_cov)
Setter |
void |
JKalman.setState_post(Matrix state_post)
Setter |
void |
JKalman.setState_pre(Matrix state_pre)
Setter |
void |
JKalman.setTransition_matrix(Matrix transition_matrix)
Getter |
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JKalman | |||||||||
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