Introduction.- Probability and Random Variables.- Convergence and Limit Theorems.- Specification of Random Processes.- Discrete-Time Finite Markov Chains.- Wiener Process and White Gaussian Noise.- Poisson Process and Shot Noise.- Processing and Frequency Analysis of Random Signals.- Ergodicity.- Scalar Markov Diffusions and Ito Calculus.- Wiener Filtering.- Quantization Noise and Dithering.- Phase Noise in Autonomous Oscillators.