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Lecture
Stochastic Models for Communications
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Stochastic Models for Communications
Covers stochastic models for communications and the estimation of correlation functions.
Modulation and Demodulation in Communication Systems
Covers modulation in communication systems, emphasizing frequency differences and signal recovery through demodulation.
Application: Error Rate of PAM Signal
Explores the impact of noise on signal transmission and the calculation of error rates in communication systems.
Linear Prediction and Estimation
Explores linear prediction, optimal filters, random signals, stationarity, autocorrelation, power spectral density, and Fourier transform in signal processing.
Signal Processing Fundamentals
Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.
Stochastic Models for Communications: Continuous-Time Stochastic Processes
Covers continuous-time stochastic processes and linear systems.
Communication Systems: Signal Transmission and Noise
Explores signal transmission, noise impact, and error probability calculations in communication systems.
Stochastic Processes for Communications: Continuous-Time Stationarity
Covers the concept of stationarity in continuous-time stochastic processes and its applications in communication systems.
Continuous-Time Stochastic Processes: Stationarity
Explores stationarity in continuous-time stochastic processes, focusing on autocorrelation and cross-correlation functions.
The success factors for digital communications
Explores the success factors behind the improvement in data transmission over the last 50 years.
