S

signal processing

Signal Viewer, Analyzer and Recorder on GPL

This project implements a BPSK (Binary Phase Shift Keying) transmitter using Software Defined Radio (SDR). The code is written to generate and transmit BPSK-modulated signals through SDR hardware such as HackRF or USRP. It allows configurable parameters like carrier frequency and bit rate, making it suitable for learning, experimentation, and research in digital communication systems.

CUDA-accelerated implementation of Partial 3D Discrete Wavelet Transform, enabling efficient multi-resolution analysis of volumetric data. Designed optimized GPU kernels to support partial inverse transform, allowing reconstruction of arbitrary points in a 3D signal without processing the entire dataset.

Python bindings for MATLAB fsst function

Physical Layer of AcubeSAT communication system.

OQPSK modulator, GMSK demodulator, ASM synchronization, Error Correction Codes (LDPC, Convolutional, BCH)

My MSc thesis work. I essayed with a number of classifiers for two type of health-related time series: electrocardiogram and blood oxygen levels. The four approaches used on each type of signal were: (i) featured based approach, where integral and differential attributes where devised and used to classify the sets (ii) Direct Machine Learning application to the time series (Perceptron, Random Forest and others) (iii) 1D convolutional neural networks applied to the signals (iv) 2D convolutional neural networks applied to the signal spectrograms.

The thesis pdf file, included here, is written in Spanish.

Python package to analyze and process time-discrete, equidistant measured signals, and visualize with Plotly

System for automatic music transcription for monophonic piano music

Methods from MNE for Python as widgets for Orange 3 https://fifal.gitlab.io/orange-mne-library/

Extract principal FFT components for features generation implemented in pytorch.

2021 interview test for optimization of Python code

Experiments for the paper: "Improving Machine Hearing on Limited Data Sets"

Comparison of standard Gabor transform with Gabor scattering audio signal representations used as an input of convolutional neural network on multiclass classification task. Experiments conducted on synthetic and GoodSounds data.

Package for computation of Gabor scattering and Mel scattering transform.