Lecture
Signal Processing: Noise Filtering and Signal Estimation
Related lectures (38)
Harmonic Signals and Spectrum Estimation
Explores harmonic signals, spectrum estimation, and signal analysis methods using MATLAB tools.
Parametric Signal Models: Matlab Practice
Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.
Signal Processing: Filtering and Noise Reduction
Explores signal-to-noise ratio, filtering noisy signals, and power spectral density for noise reduction in signal processing.
Noise in Electronics
Introduces the fundamentals of noise in electronics, covering origins, signal types, power characteristics, and noise sources.
Spectral Estimation Methods
Explores parametric spectrum estimation methods, including line and smooth spectra, and delves into heart rate variability analysis.
Electrical Metrology
Explores different types of noise in electrical systems and their impact on electronic devices.
Signal Processing Fundamentals
Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.
Coherent Detection: Signal and Local Oscillator Interference
Explores coherent detection in optical systems, highlighting the interference between the signal and local oscillator.
Laser Systems
Covers the fundamental concepts of laser operation, including dispersion theory, gain and resonators, different types of laser systems, noise characteristics, optical fibers, ultrafast lasers, and nonlinear frequency conversion.
Poisson Process: Impulsive Noise
Covers the Poisson process, focusing on impulsive noise and shot noise models.