Signal Processing

Cute Fourier Transformation coming ! Fourier transformation $X(t)$ is the amplitude-time function, we want to transform this into frequency domain. Typically, we want to decompose the function into several sine and cosine function with different frequency, phase and amplitude. $F$ represents the frequency we focus on. $$X(F) = \int_{-\infty}^{+\infty} X(t) e ^{-i2\pi Ft}dt$$ The dot product verifies the similarity of the analysis function and the amplitude-time function. Discrete Fourier transformation When we can only sample data from the signals, we replace the X with the folowwing....

We developed a learning-based automatic localizer to accurately identify hippocampal sublayer in mice from high-density extracellular recordings by aligning neural manifolds across sessions and animals.

DeepSeparator is a deep learning framework designed to separate neural signals from artifacts in EEG recordings and reconstruct clean signals.