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The main scope of this app is to collect raw data, processing them into usable data, measure varius indicators and export final results to create useful conclusions concerning of the needs of the reaserch..
Digital Audio Filtering Project: A Python-based toolkit for manipulating and analyzing audio signals, offering time and frequency domain visualizations and customizable filtering options.
Designed Bandpass and Bandstop IIR filters using the Butterworth, Chebyschev and Elliptic approximation. Also designed Bandpass and Bandstop FIR filters using the Kaiser Window to compute the coefficients of impulse response
Elegant Butterworth and Chebyshev filter implemented in C, with float/double precision support. Works well on many platforms. You can also use this package in C++ and bridge to many other languages for good performance.
In this project, low-pass filters and Kalman filters with different window function designs are used to denoise speech signals polluted in the full frequency band of Gaussian white noise