ptichko
Parker Tichko, PhD. Cognitive scientist, musician, and composer interested in the dynamics of cognition, music, language, and development.
Pinned Repositories
Adaptive-Frequency-Oscillators
MATLAB implementation of Righett et al., (2006). Work in progress.
fractal-melodies
Generates fractal melodies using the method described by Beauvois (2007), Music Perception (DOI: 10.1525/mp.2007.24.3.247).
MOG-Tutorial
A tutorial using the R library Mixtools to model infants' statistical learning of speech sound categories. The statistical model is a MOG whose parameters are estimated using the EM algorithm. First, a model is introduced to estimate parameters of VOT distrbutions for voiced/voiceless speech sounds using EM. Then, a hypothesis testing approach is introduced to determine the number of components/categories. The model is loosely based off of McMurray et al. (2009), Developmental Science, and Kuhl et al. (1997).
ptichko
Config files for my GitHub profile.
ptichko.github.io
Personal Website
ptichko.github.io_older
Code that'll help you kickstart a personal website that showcases your work as a software developer.
RomanKoshkin
Single-Layer-Network-with-Hebbian-Learning
A single-layer gradient-frequency neural network based off of Tichko & Large (2019) (https://doi.org/10.1111/nyas.14050).
Theoretical-FFR
Matlab scripts to generate theoretical frequency-following resonses (FFRs). See Tichko & Skoe (2017) (https://doi.org/10.1016/j.heares.2017.01.014) for model details.
Two-Layer-Network-with-Hebbian-Learning
Two-layer oscillatory neural network with Hebbian plasticity.
ptichko's Repositories
ptichko/Adaptive-Frequency-Oscillators
MATLAB implementation of Righett et al., (2006). Work in progress.
ptichko/MOG-Tutorial
A tutorial using the R library Mixtools to model infants' statistical learning of speech sound categories. The statistical model is a MOG whose parameters are estimated using the EM algorithm. First, a model is introduced to estimate parameters of VOT distrbutions for voiced/voiceless speech sounds using EM. Then, a hypothesis testing approach is introduced to determine the number of components/categories. The model is loosely based off of McMurray et al. (2009), Developmental Science, and Kuhl et al. (1997).
ptichko/Two-Layer-Network-with-Hebbian-Learning
Two-layer oscillatory neural network with Hebbian plasticity.
ptichko/fractal-melodies
Generates fractal melodies using the method described by Beauvois (2007), Music Perception (DOI: 10.1525/mp.2007.24.3.247).
ptichko/ptichko
Config files for my GitHub profile.
ptichko/ptichko.github.io
Personal Website
ptichko/ptichko.github.io_older
Code that'll help you kickstart a personal website that showcases your work as a software developer.
ptichko/RomanKoshkin
ptichko/Single-Layer-Network-with-Hebbian-Learning
A single-layer gradient-frequency neural network based off of Tichko & Large (2019) (https://doi.org/10.1111/nyas.14050).
ptichko/Theoretical-FFR
Matlab scripts to generate theoretical frequency-following resonses (FFRs). See Tichko & Skoe (2017) (https://doi.org/10.1016/j.heares.2017.01.014) for model details.
ptichko/spleeter
Deezer source separation library including pretrained models.
ptichko/startbootstrap-resume
A Bootstrap 4 resume/CV theme created by Start Bootstrap