| Package | Description |
|---|---|
| mikera.matrixx.algo | |
| mikera.matrixx.decompose | |
| mikera.matrixx.decompose.impl.svd |
| Modifier and Type | Method and Description |
|---|---|
static int |
Rank.compute(ISVDResult result)
Directly computes rank of matrix whose SVD decomposition has already been computed.
|
static int |
Rank.compute(ISVDResult result,
double threshold)
Directly computes rank of matrix whose SVD decomposition has already been computed.
|
| Modifier and Type | Method and Description |
|---|---|
static ISVDResult |
SVD.decompose(AMatrix A)
Computes the Singular Value Decomposition of a matrix, which is the decomposition
of the given matrix A as:
A = U*S*V,
where U and V are orthogonal and S is a diagonal matrix containing singular values
along its diagonal.
|
static ISVDResult |
SVD.decompose(AMatrix A,
boolean compact)
Computes the Singular Value Decomposition of a matrix, which is the decomposition
of the given matrix A as:
A = U*S*V,
where U and V are orthogonal and S is a diagonal matrix containing singular values
along its diagonal.
|
static ISVDResult |
SVD.decomposeCompact(AMatrix A)
Computes the Singular Value Decomposition of a matrix, which is the decomposition
of the given matrix A as:
A = U*S*V,
where U and V are orthogonal and S is a diagonal matrix containing singular values
along its diagonal.
|
| Modifier and Type | Class and Description |
|---|---|
class |
SVDResult |
| Modifier and Type | Method and Description |
|---|---|
static ISVDResult |
ThinSVD.decompose(AMatrix a) |
static ISVDResult |
ThinSVD.decompose(Matrix matrix) |
Copyright © 2016. All rights reserved.