Gaussian Processes: Designing Receivers

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By Emre Telatar explores binary hypothesis testing and decision rule design.

Explores Bayesian estimation for unsupervised learning and MCMC, using a Spin Glass Card game example.

Covers the concepts of spin glasses and Bayesian estimation, focusing on observing and inferring information from a system closely.

Explores neural signals, EMG control, muscle synergies, and HD-EMG for prosthetic devices.

Explores heart rate variability analysis using ECG data and its physiological significance.

Explores Maximum Likelihood Estimation properties, consistency, and applications in statistical inference.

Delves into neural signals, GLM, ANOVA, brain mapping, connectivity, and multivariate methods.

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.

Covers hypothesis testing with Gaussian noise and the standard Gaussian distribution.