Concept

White noise

Related lectures (32)

Introduces the fundamentals of noise in electronics, covering origins, signal types, power characteristics, and noise sources.

Noise in Devices and Circuits

Explores different types of noise in devices and circuits, including interference noise, inherent noise, and random signals.

Untitled

Stochastic Models for Communications: Continuous-Time Stochastic Processes

Covers continuous-time stochastic processes and linear systems.

Stochastic Processes and Spectral Densities

Covers spectral densities, signal correlations, and white noise processes in stochastic systems.

Parametric Signal Models: Matlab Practice

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Noise in Electronics: Fundamentals and Applications

Explores noise in electronics, covering average power, signal-to-noise ratio, deterministic and random signals, and noise amplification.

White Gaussian Noise in Communication Systems

Covers White Gaussian Noise in communication systems and its impact on signal transmission.

Stochastic Models for Communications

Covers stochastic models for communications, including stationarity, ergodicity, power spectral density, and Wiener filter.

Time Series Models: Autoregressive Processes

Explores time series models, emphasizing autoregressive processes, including white noise, AR(1), and MA(1), among others.

Linear Estimation and Prediction: Part 2

Covers the estimation and prediction of random signals in linear systems.

Untitled

Laser Systems: Theory and Applications

Covers modules on laser systems, including basic operation, noise characteristics, and modern applications.

Communication Channels: Gaussian Noise and Capacity

Explores the capacity of communication channels with Gaussian noise and noise impact.

Stochastic Processes: Basics & Stationarity

Covers signal generation, statistical relations, stationarity, white noise, and orthogonality in stochastic processes.

Power spectral density and noise correlations

Explores power spectral density, noise correlations, correlation functions, and classical noise categories.

Time Series: Spectral Estimation & Yule Walker

On Time Series explores Spectral Estimation, Yule Walker method, and ARIMA models.

Linear Estimation and Prediction

Explores linear estimation, Wiener filters, and optimal prediction in signal processing.

Laser Systems: Theory and Modern Applications

Covers various modules related to laser systems, including the basics of laser operation, different types of lasers, noise characteristics, and applications in modern technology.

Time Series: Fundamentals and Models

Explores the fundamentals of time series analysis, including stationarity, linear processes, forecasting, and practical aspects.