Optimization of sigma-delta modulator based on artificial immune algorithms

The artificial immune algorithms are implemented by the human immune system. They inspired a technique that has the ability to find optimal solutions in a nonlinear search space. This kind of technique increases the computing speed and converges faster than the genetic algorithms. In this paper is presented an application of artificial immune algorithms in order to optimize the transfer function of a sigma delta modulator. It is also presented the base method which can perform the adjustment coefficients, in decimal, of the sigma delta modulator. The results are compared with those obtained by the method of optimization based on both mathematical and genetic algorithms.