Deep Recurrent Neural Networks for Source Separation
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Updated
Jul 21, 2021 - MATLAB
Deep Recurrent Neural Networks for Source Separation
Efficient, transparent deep learning in hundreds of lines of code.
Ensemble RNN based neural network for ECG anomaly detection
Platform + GUI for hyperparameter optimization of recurrent neural networks (MATLAB).
Generalized Implementation of RNNs for Chaotic Time Series Prediction
Computational Neuroscience projects.
This project uses Recurrent Neural Networks (RNNs) to classify the behavior of objects in traffic based on their risk level, enhancing the safety of autonomous vehicles. Developed as part of the MATLAB-Simulink Challenge by MathWorks.
Development of a spinal pattern generator (SPG) model to predict muscle activations at the ankle joint during walking
Classify 6 types of human activity from time series sensor data
Machine learning ( RNN (Recurrent Neural Network) and SVM (Support Vector Machine) ) recognition/classification of 7 hand gestures using 6 channels of BioRadio 150 & BioCapture
Code for Computational Neuroscience course 2020/2021 @ UniPi
University Project for "Intelligent Systems" course (MSc Computer Engineering @ University of Pisa). ECG Fitting, Forecasting and Activity Classification using NN, CNN, RNN and Fuzzy Systems.
This library instantiates an RNN to solve Newsome & Shadlin's task -- two types of input and a context to decide which to attend. It does so with an itinerating attractor network.
Computational Neuroscience models
Details of certified courses covered by me. Includes notes and solutions to programming exercises.
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