caxenie Goto Github PK

artemic

ARTEMIC = Advanced Real-time Embedded Mobile robot Intelligent ControllerReal-time Linux fault tolerant control application for mobile robots. Multi-level control application: Fuzzy Sliding-Mode kinematic controller, EKF fault tolerance module and ultrasound based SLAM module.

basecamp-winterschool-2017

Lectures and labs from BaseCamp DATA SCIENCE TRAINING PROGRAM.

bigdata-streaming-demo

End-to-End example with Big Data tools. Data from a Sumo simulation are sent to Kafka, processed by Flink, and real-time plotted by matplotlib.

caxenie.github.io

chimera

CHIMERA: Combining Mechanistic Models and Machine Learning for Personalized Chemotherapy and Surgery Sequencing in Breast Cancer

code-snippets

Various code snippets

corr-learn-som

Simple implementation of the distributed cognitive maps for environment interpretation.

corr-learn-som-fast

Simple implementation of the distributed cognitive maps for environment interpretation. Use artificial data selected / given by user. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints. The constraints are learned through biologically plausible mechanisms from data.

corr-learn-som-python

Simple implementation of the distributed cognitive maps for environment interpretation. Use artificial data selected / given by user. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints. The constraints are learned through biologically plausible mechanisms from data. Sensory correlation learning neural network. Unsupervised learning of functional relationships between 2 input sensory streams. The network uses SOMs to encode the input data into a population code and Hebbian learning to extract the co-activation patterns encoding the function. Python implementation.

corr-learn-som-python-demo

About Unsupervised learning of relations following the network combining WTA, HL and HAR over the projections sharpening architecture. Python jupyter demo.

corr-learn-som-quadrotor

Quadrotor implementation of the distributed cognitive maps for environment interpretation. Use artificial data selected / given by user. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints. The constraints are learned through biologically plausible mechanisms from data. Sensory correlation learning neural network. Unsupervised learning of functional relationships between 2 input sensory streams. The network uses SOMs to encode the input data into a population code and Hebbian learning to extract the co-activation patterns encoding the function. Datasets from quadrotor system.

cristianaxenie.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

customer-churn-fis-predictor

Customer churn prediction using Fuzzy Inference Systems.

dev-sensor-fusion-net

Unsupervised sensory correlation learning using Self-Organizing-Maps for sensor fusion. Each sensory variable projects onto a SOM network which depending on the global network connectivity (1, 2, ... , N vars) connects to other SOM associated with other sensory variables. Extension to extract also temporal correlations using a recursive architecture.

developing-fusion-network-fast

Simple implementation of the distributed cognitive maps for environment interpretation. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints. The constraints are learned through biologically plausible mechanisms from data. Sensory correlation learning neural network. Unsupervised learning of functional relationships between 2 input sensory streams. The network uses SOMs to encode the input data into a population code and Hebbian learning to extract the co-activation patterns encoding the function. Modelling human circuitry development for multisensory integration. C code implementation.

dynamic-association-net

Dynamic association model to learn correlations between paired modalities samples acquired from different sensors current scenario is using only 2 input modalities.

electric-imp-wifi-dev

Test eimp throughput for NST WiFi modules interfacing.

embedded-ser2eth-converter

Simple embededed serial (USART) to Ethernet (TCP/IP) converter using AVR32 and ATMega16 platforms. Development scheme for industrial automation and supervisory control and distributed data acquisition systems.

emokit-bci-interface

Fork of emokit with addon for the Neural Engineering class @ TUM

fall-detector

Hack Cambridge 2017 - Real-time Event-based Monitoring System for Seniors and Elderly using Neural Networks

feature-extraction-intro

Feature-Extraction - Theoretische Grundlagen, Methodik und Umsetzung in der Medizin (Brustkrebs-Datenanalyse)

features-selection-intro

Einführung in die Feature-Auswahl für die Data Science Pipeline

fusion-maps-analyzer

Simple implementation of the distributed cognitive maps for environment interpretation. Use artificial data selected / given by user. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints.

fusion-maps-analyzer-matlab

Simple implementation of the distributed cognitive maps for environment interpretation. Use artificial data selected / given by user. The input activity mildly influences the belief of the cortically inspired relaxation network. The network dynamics ensures convergence to a stable state in which all quantities are in agreement given the mathematical constraints. Matlab version for easy prototyping and parametrisation.

fusion-maps-population-code

Demo software usign population code for estimating arbitrary functions. The setup contains 2 input populations each coding some scalar (unimodal) variable which are projected onto a 2D network of units with neurons exhibiting short range excitation and long range inhibition dynamics. The ouput from the intermediate layer is projected to an output population the network has no explicit input and output as each of the populations may be considered inputs / outputs and the processing happens in the intermediate layer.

fuzzy-ctrl-demo

Trajectory tracking control for wheeled mobile robots in a robot soccer field using Fuzzy Logic.

garmin-tracker-analytics

Garmin Activity Tracker Datenanalyse

gas-antenna-demo

Sample demo software for Genetic Algorithms for RF antenna design. The task is to find an optimal wire antenna design (shape) knowing the number of points, the frequency and the desired gain.

gas-opt-demo

Simple Genetic Algorithm for function optimization demo.

gas-tsp-demo

Sample demo software for Genetic Algorithms for solving Traveling Salesman Problem.