Neurobiological Signal Processing

Related lectures (32)

Page 3 of 4

Introduces continuous time Markov chains on a finite state space with exponential waiting times and jump probabilities.

Explores neural signals, EMG processing, muscle synergies, and prosthetic control using advanced signal processing techniques.

Explores power spectral density, Wiener-Khintchine theorem, ergodicity, and correlation estimation in random signals for signal processing.

Explores the Discrete Fourier Transform applied to signals of unlimited duration using various windows for improved accuracy.

Covers Gaussian Mixture Models, Denoising, Data Classification, and Spike Sorting using Principal Component Analysis.

Explores the advancements and challenges in neuromorphic electronic skins, aiming to enable intuitive use of replacement limbs and autonomous robots.

Discusses signal representation, focusing on mathematical expressions and inequalities in signal processing.

Explores neural activity, electromagnetic signals, EEG, MEG, signal properties, noise sources, analysis methods, and decoding techniques.

Explores neural signal processing methods, fMRI designs, GLM analysis, and quality control.

Explores IQ demodulation using FPGA and MATLAB for noisy quantum signals.