Related lectures (63)
Rainfall Models: Deterministic vs Stochastic
Covers deterministic and stochastic rainfall models in water resources engineering, including generation, calibration, and spatially explicit models.
Stochastic Models for Communications
Covers stochastic models for communications, including Poisson processes and counting processes.
Elements of Statistics: Memorylessness, Stationary Processes, Estimation using MLE
Explores memorylessness in distributions, stationary processes, and estimation using MLE.
Neurobiological Signal Processing
Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
Modeling Neurobiological Signals: Spikes & Firing Rate
Explores modeling neurobiological signals, focusing on spikes, firing rate, multiple state neurons, and parameter estimation.
Markov Chains: Basics and Applications
Introduces Markov chains, covering basics, generation algorithms, and applications in random walks and Poisson processes.
Stochastic Models for Communications
Covers mathematical tools for communication systems and data science, including information theory and signal processing.
Stochastic Processes: Generation and Embedding
Explores the generation of stochastic processes, including Gaussian processes, Markov processes, Poisson processes, and circulant embedding.
Stochastic Models for Communications
Covers the fundamentals of stochastic models for communications, focusing on Markov chains and Poisson processes.
Poisson Processes: Examples
Explores Poisson processes through examples and proofs, discussing customer arrivals in a store and related probabilities.

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