Quantization: Basics and Uniform Input

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Explores hardware technologies, quantum electronics, cryogenic systems, quantum computing, and ADC architectures.

Explores spectral estimation for Gaussian and binary signals in the spiked matrix estimation problem, analyzing the impact of signal-to-noise ratio.

Explores quantization and coding of digital signals, discussing uniform quantization, error analysis, and signal-to-quantization noise ratio.

Explores ADCs fundamentals for IoT smart sensors, covering quantization, non-idealities, and topologies.

Explores quantum and nanocomputing, covering feedback amplifiers, ADCs, noise limitations, and ADC architectures.

Explores analog and digital signal processing, A/D and D/A conversion, resolution, settling time, and digital interfaces in electronic circuits.

Explores noise reduction techniques in electrical systems, covering concepts like Fourier transform, impedance matching, and dithering.

Explores digital design principles, ADC architectures, FPGA-based ADCs, figures of merit, and lower bounds in digital design.

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

Discusses various noise sources in optical detectors, including shot noise, thermal noise, and their implications on detection performance.