: Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms d...
We discuss a theory for a realistic, applicable scaled genetic algorithm (GA) which converges asymptoticly to global optima in a coevolutionary setting involving two species. It is...
The proportionate normalized least-mean squares (PNLMS) adaptation algorithm exploits the sparse nature of acoustic impulse responses and assigns adaptation gain proportional to t...
The average consensus problem in the distributed signal processing context is addressed by linear iterative algorithms, with asymptotic convergence to the consensus. The convergen...
In this paper, we analyze the convergence of an iterative selftraining semi-supervised support vector machine (SVM) algorithm, which is designed for classi cation in small trainin...