The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimization of the centers and widths of the kernels. The aim is to optimize the likelihood that the given data points are generated by a mixture of Gaussians. The numbers next to the Gaussians give the relative importance (amplitude) of each component.
This program is using Genetic algorithm to solve the Travlling
Salesman Problem. It gives the best path route within a specified
time.
usage: java Evolver <seconds> <city file> <config file>
Author: Liu Yang
The decoding algorithm used in RBDS.c is based on error trapping. The program emulates the operation of the encoder and decoder of a binary cyclic codes, using bitwise shifts and xor for modulo g(x) operations.
The Viterbi algorithm is the same as the binary case with one main difference: The survivor sequences include the uncoded bits, which are decided at each trellis stage when selecting one of two parallel branches with the largest correlation metric.
Presently, only 8-PSK modulation is considered. Extensions to higher-order modulations can be implemented following a similar procedure.
