dkohlsdorf

public class LongestCommonSubsequence {

	public static int length(String x, String y) {
		int N = x.length();
		int M = y.length();
		int lcs[][] = new int[N + 1][M + 1];
		
		for(int i = 1; i < N + 1; i++) {
			for(int j = 1; j < M + 1; j++) {

dkohlsdorf

public class RecerseAString {

	public static String reverse(String string) {
		char str[] = string.toCharArray();
		for(int i = 0; i < str.length / 2; i++) {
			char tmp = str[i];
			str[i] = str[str.length - 1 - i];
			str[str.length - 1 - i] = tmp;
		}

dkohlsdorf

public class BinarySearch {

	public static int search(int[] sorted, int element) {
		int min = 0;
		int max = sorted.length;
		while(max > min) {
			int mid = min + (max - min) / 2;
			if(sorted[mid] == element) {
				return element;

dkohlsdorf

package prediction;

import org.apache.commons.math3.linear.Array2DRowRealMatrix;
import org.apache.commons.math3.linear.ArrayRealVector;

/**
 * Item based interpolation
 * 
 * @author Daniel Kohlsdorf
 */

dkohlsdorf

package analysis.preprocessing;

import java.util.HashMap;
import java.util.Vector;

import database.OhuraDB;
import database.indexing.LocalFeature;

/**
 * Topic Modeling using the Latent Dirichlet

dkohlsdorf

package processing.utils;

/**
 *   Utilities to compute log probabilities
 *
 *   @author Daniel Kohlsdorf
 */
public class ProbabilityUtils {
    
    public static final double ZERO = Double.NEGATIVE_INFINITY;

dkohlsdorf

package processing.signals;

import java.util.ArrayList;

import processing.utils.ProbabilityUtils;

/**
 * Viterbi Style Whistle Tracing
 *
 * @author Daniel Kohlsdorf

dkohlsdorf

package processing.inference;

import java.util.ArrayList;
import java.util.Vector;

import processing.model.Gaussian;
import processing.model.GaussianMixture;
import processing.model.HiddenMarkovModel;
import processing.model.ProbabilityDistibution;
import processing.utils.ProbabilityUtils;

dkohlsdorf

package processing.inference;

import java.util.ArrayList;

import processing.model.HiddenMarkovModel;
import processing.utils.ProbabilityUtils;


/**
 * Inference algorithms used for training and decoding hidden markov models.

dkohlsdorf

package processing.segmentation;

import java.util.ArrayList;

/**
 * Compute the Dynamic Time Warping Distance 
 *
 * @author Daniel Kohlsdorf
 */
public class DynamicTimeWarping {