FPGA Implementation of an Adaptive Filter Robust to Impulsive Noise: Two Approaches

Simulink Modeling and Design of an Efficient Hardware-Constrained FPGA-Based PMSM Speed Controller

“…As this design methodology resembles to software development, it has been proven to lead to a similar degree of faults in the implementation [30]. However, modern design tools, like LabView FPGA [17], [31], DSP Builder [23] or System Generator [32], [33] are gaining momentum. It has been proven [32] that System Generator can lead to comparable results in terms of obtained speed as HDL description for complex designs.…”

“…It has been proven [32] that System Generator can lead to comparable results in terms of obtained speed as HDL description for complex designs. In [33], both the VHDL and the System Generator designs of an adaptive filter show similar performance in terms of speed and area. This paper will thus try to fill in the gap found in the existing literature: it proposes a holistic modeling of a permanent magnet synchronous machine (PMSM) speed control system in the Matlab Simulink environment, which allows validation by simulation of the controller model, as well as of the FPGA hardware; it also takes into account severe hardware constraints, leading to a very low cost FPGA implementation.…”

A nonparametric Bayesian model for system identification based on a super‐Gaussian distribution

“…Methods for estimation of coefficients of an unknown FIR function proposed in Refs. use evaluation functions derived through integration of tanh(⋅) and multiplying it by a constant.…”

“…When logarithm of hyperbolic secant distribution is differentiated with respect to a random variable, tanh(⋅) is obtained; that is, assumption about hyperbolic secant distribution of noise is related to methods in Refs. .…”

Adaptive recursive algorithm with logarithmic transformation for nonlinear system identification in α -stable noise

“…Many methods were presented to describe the probability density function (PDF) of impulsive noise, such as Gaussian mixture model (GMM) [20], contaminated Gaussian (CG) model [21][22][23][24], etc. By using robust mixed-norm [21], robust M-estimate method [20], [22][23][24] and so on, it solves the performance deterioration of adaptive filter in these impulsive model environments. Alternatively, the Į-stable distribution also provides a valid model for this type of signals [25][26].…”