An exhaustive review on the use of structured stochastic search approaches towards system
identification and digital filter design is presented in this paper. In particular, the paper …

The number of publications related to complex-valued encoding metaheuristic optimization
research is increasing the area of metaheuristic optimization is gaining in popularity. In this …

Conventional derivative based learning rule poses stability problem when used in adaptive
identification of infinite impulse response (IIR) systems. In addition the performance of these …

Since the error surface of digital infinite-impulse-response (IIR) filters is generally nonlinear
and multimodal, global optimization techniques are required in order to avoid local minima …

Particle swarm optimisation (PSO) has been enormously successful. Within little more than a
decade hundreds of papers have reported successful applications of PSO. In fact, there are …

In this paper, swarm and evolutionary algorithms have been applied for the design of digital
filters. Particle swarm optimization (PSO) and differential evolution particle swarm …

The contrive principle of the adaptive infinite impulse response (IIR) filter is to find the filter
parameters based on the error function, thus obtaining the best model of the unbeknown …

System identification is a challenging and complex optimization problem due to nonlinearity
of the systems and even more in a dynamic environment. Adaptive infinite impulse response …

The uni-modal error surfaces and intrinsic stable behaviors of adaptive finite impulse
response (FIR) filters make gradient based algorithms very effective in the design of these …

This paper presents a cuckoo search algorithm (CSA) based adaptive infinite impulse
response (IIR) system identification scheme. The proposed scheme prevents the local …