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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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