Spectral Estimation: Gaussian vs Binary Signals

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Explores quantization in digital devices, covering scalar and uniform quantization, mean square error, and signal-to-noise ratio.

Covers wireless receivers in the presence of Gaussian noise and error probability estimation.

Discusses the formalism of noise in photodetectors, focusing on detection limits and the relationship between input power and output current.

Explores linear estimation and prediction in AR parametric models, focusing on Yule Walker equations and Wiener filter.

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

Explores noise in optical receivers, covering shot noise, thermal noise, signal-to-noise ratio, and noise limits.

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.

Covers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.

Explores Poisson processes in communication systems, focusing on photodetectors and signal-to-noise ratio calculations.

Explores noise filtering, signal estimation, and signal-to-noise ratio optimization through Wiener-Khintchine theorem and power spectral density.