Impact of Sinusoidal Sum Terms

Related lectures (30)

Page 3 of 3

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

Covers the basic definitions and typology of signals, including analog and digital signals.

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

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

Explores the sampling theorem, illustrating signal reconstruction and the importance of meeting the Nyquist criterion.

Explores neural signal processing for brain-computer interfaces, including decoding techniques like Kalman filters and spike sorting.

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

Explores expressing signals in sinusoidal components and decomposing signals into different frequencies in the frequency domain.

Explores harmonic signals, spectrum estimation, and signal analysis methods using MATLAB tools.

Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.