Covers the basics of numerical analysis, including adaptive feature computation, residual analysis, and the importance of well-posed problems.
Introduces the fundamentals of vectors in C++, covering initialization, direct access, range-for loop, and specific functions.
Covers the density operator formalism, polynomial time, NP problems, BPP, QMA, and probabilistic algorithms.
Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.
Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.
