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/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/
/**
* Matrix interface, dense and sparse (band or irregular) matrix encapsulation
* classes, LU, QR, Cholesky, SVD and eigen decompositions, etc. A matrix
* is a rectangular array of numbers, symbols, or expressions. The individual
* items in a matrix are called its elements or entries.
*
* One of most important matrix operations is the matrix vector
* multiplication, which is the only operation needed in many iterative matrix
* algorithms, e.g. biconjugate gradient method for solving linear equations and
* power iteration and Lanczos algorithm for eigen decomposition, which are
* usually very efficient for very large and sparse matrices.
*
* @author Haifeng Li
*/
package smile.math.matrix;
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