Uniform quantization is a process used in digital signal processing where a continuous range of values is mapped to a finite set of discrete levels, ensuring equal spacing between each quantization level. It is commonly used in analog-to-digital conversion to simplify the representation of signals, although it may introduce quantization noise due to the rounding of values.

Uniform Quantization

Uniform quantization

Digital Signal Processing (DSP) involves the manipulation of signals to improve or modify their characteristics, enabling efficient data transmission, storage, and analysis. It is fundamental in various applications like audio and speech processing, telecommunications, and control systems, leveraging algorithms to perform operations such as filtering, compression, and feature extraction.

digital signal processing

continuous range of values

finite set of discrete levels

Equal spacing between quantization levels

Analog-to-Digital Conversion (ADC) is the process of converting continuous analog signals into discrete digital numbers, enabling digital systems to process real-world signals. This conversion is crucial for digital devices to interpret and manipulate data from the physical world, such as sound, temperature, and light, with applications spanning from audio recording to sensor data processing.

analog-to-digital conversion

representation of signals

Quantization noise is the error introduced when mapping a large set of input values to a smaller set, such as in digital signal processing where continuous signals are converted to discrete digital values. This noise is inherent in the quantization process and can affect the accuracy and quality of digital representations of analog signals.

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