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* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.
*/
package org.apache.commons.math4.transform;
/**
* This enumeration defines the various types of normalizations that can be
* applied to discrete Fourier transforms (DFT). The exact definition of these
* normalizations is detailed below.
*
* @see FastFourierTransformer
* @since 3.0
*/
public enum DftNormalization {
/**
* Should be passed to the constructor of {@link FastFourierTransformer}
* to use the <em>standard</em> normalization convention. This normalization
* convention is defined as follows
* <ul>
* <li>forward transform: y<sub>n</sub> = &sum;<sub>k=0</sub><sup>N-1</sup>
* x<sub>k</sub> exp(-2&pi;i n k / N),</li>
* <li>inverse transform: x<sub>k</sub> = N<sup>-1</sup>
* &sum;<sub>n=0</sub><sup>N-1</sup> y<sub>n</sub> exp(2&pi;i n k / N),</li>
* </ul>
* where N is the size of the data sample.
*/
STANDARD,
/**
* Should be passed to the constructor of {@link FastFourierTransformer}
* to use the <em>unitary</em> normalization convention. This normalization
* convention is defined as follows
* <ul>
* <li>forward transform: y<sub>n</sub> = (1 / &radic;N)
* &sum;<sub>k=0</sub><sup>N-1</sup> x<sub>k</sub>
* exp(-2&pi;i n k / N),</li>
* <li>inverse transform: x<sub>k</sub> = (1 / &radic;N)
* &sum;<sub>n=0</sub><sup>N-1</sup> y<sub>n</sub> exp(2&pi;i n k / N),</li>
* </ul>
* which makes the transform unitary. N is the size of the data sample.
*/
UNITARY;
}