Stochastic Models for Communications

Related lectures (32)

Page 3 of 4

Covers energy resolution, detector behavior, dead time, creation of electron-ion pairs, and detection regions in gas detectors.

Explores coherent detection in optical systems, highlighting the interference between the signal and local oscillator.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Explores signal-to-noise ratio, filtering noisy signals, and power spectral density for noise reduction in signal processing.

Introduces Markov chains, covering basics, generation algorithms, and applications in random walks and Poisson processes.

Explores nonlinear coupling in a beam, covering device fabrication, actuation, detection, noise separation, and signal-to-noise ratio.

Explores high energy photon detection principles, efficiency, CCD detectors, Anti-Reflective coatings, and Signal to Noise ratio.

Discusses the formalism of noise in photodetectors, focusing on detection limits and the relationship between input power and output current.

Explores achievable rate, capacity, power efficiency, spectral efficiency, and error probabilities in communication systems.

Explores spectral estimation for Gaussian and binary signals in the spiked matrix estimation problem, analyzing the impact of signal-to-noise ratio.