spike-detection
There are 18 repositories under spike-detection topic.
ramintoosi/ROSS
Robust Offline Spike Sorter
HelmchenLabSoftware/Cascade
Calibrated inference of spiking from calcium ΔF/F data using deep networks
akcarsten/spike_sorting
Python implementation of signal processing techniques and K-means clustering to sort spikes.
ajayarunachalam/pynmsnn
NeuroMorphic Predictive Model with Spiking Neural Networks (SNN) using Pytorch
mhhennig/HS2
Software for high density electrophysiology
nghorbani/NeuralDataAnalysis
Download Data from https://bit.ly/3g8RUmi
tbrouns/paser
PASER: Processing and Analysis Schemes for Extracellular Recordings
michaela10c/neural_spike_detection
Python Jupyter notebook for Neuralink Patent No. US 2021/0012909 A1, titled "Real-Time Neural Spike Detection"
firelord97/Spike-Detection-using-Neural-Nets
Neural network-based approach for detecting spikes in high-density neural data using Multi-Layer Perceptron models
konstantd/Biomedical_Engineering
Digital Signal Processing in Electroencephalography signals. Spike detection with threshold method and isolation with windowing. Temporal and spectral feature extraction. Classification in three neurons.
libo-huang/Unified-SS
[TNSRE-2021] Official implementation of "A Unified Optimization Model of Feature Extraction and Clustering for Spike Sorting"
RezaSaadatyar/Spike-Sorting-Techniques
This repository includes useful MATLAB codes for ENG analysis.
W-orko/NSpike
MATLAB GUI to identify, extract and analyze neural electrode data for action potentials by isolating neural spikes from noise.
gavinmischler/spikeFRInder
Spike inference algorithm using frequency-domain FRI framework
lkct/hs-detection
Optimized spike detection based on https://github.com/mhhennig/HS2
tivenide/SpikeSense
ML workflow designed for processing neurophysiological MEA data
ydecastro/super-resolution-testing
Testing procedures for Super-Resolution, i.e. testing spikes from low frequency measurements.
marinimau/Spike-detection-for-cooking-activity-recognition-based-on-indoor-air-quality-sensor
Lo scopo dell'applicazione è quello di costruire un feature vector per la predizione dei pasti in base a valori registrati da sensori di qualità dell'aria. Le feature prodotte verranno automaticamente unite a feature statistiche già presenti in alcuni files. Per la classificazione utilizzare il Knowledge Flow Enviroment di Weka impostato nel file allegato.