Discrete time and continuous time

Related lectures (30)

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Explores the transition from analog to digital control systems using microprocessors.

Covers the dynamics of discrete systems and the concept of orbits in Riemann varieties.

Covers the fundamental properties of systems in discrete and continuous time domains.

Explores complex random vectors, stationarity, ergodicity, and the analysis of signals.

Explores the stability of networked control systems under packet loss and stochastic dropouts, emphasizing mean-square stability and robustness.

Explores Z-transform, system properties, and analysis of discrete systems, focusing on stability and transfer functions.

Explores statistical properties, signal representation, discrete signals, and binary signals.

Covers the concepts of analog, discrete, and digital signals, sampling times, frequencies, and pulses.

Explores the generation of stochastic processes, including Gaussian processes, Markov processes, Poisson processes, and circulant embedding.

Explores discrete signals, linear systems, categorization examples, and convolution properties in signal processing.