Real-time window function design for finite impulse response digital filter in Labview with particle swarm optimization algorithm

During Finite Impulse Response (FIR) digital filter design using the Fourier Series method, window functions are used to eliminate unwanted Gibbs oscillations in the cut-off frequency domain. The design of window functions has been performed using many methods in the literature. In this thesis, two different adjustable window function designs are presented with LabVIEW, which provides a powerful graphical programming environment that is remote from the complexity. At the same time, an alternative cosh window function design was implemented in MATLAB using Particle Swarm Optimization (PSO). Utilizing LabVIEW's parallel programmability feature, the cosh window function design data, implemented using Particle Swarm Optimization (PSO), has been exported to the LabVIEW environment and FIR digital filter design has been realized with window functions realized by different methods of designs. The designed FIR digital filters filtered the EEG signal whose it is transferred to the LabVIEW environment, and the results are displayed in real time by DAQ (Data Acquisition) card. The amplitude spectrum of the designed window functions at different parameter values were observed and interpreted. Keywords: LabVIEW, Window Functions, Design of FIR Filter, Particle Swarm Optimization (PSO)