kvantiseringsschemata

Kvantiseringsschemata, often translated as quantization schemes, are methods used in digital signal processing and information theory to represent continuous or a large number of discrete values with a smaller set of discrete values. This process is fundamental to converting analog signals into a digital format, which is essential for storage, transmission, and processing by digital systems.

The core idea behind quantization is to map a range of input values to a single representative output value. This inevitably introduces an error, known as quantization error or quantization noise, because the original value is not perfectly represented. The choice of quantization scheme significantly impacts the fidelity of the digital representation and the amount of error introduced.

Common quantization schemes include uniform quantization, where the quantization levels are equally spaced, and non-uniform quantization, where the spacing varies. Non-uniform schemes are often employed when the input signal has a non-uniform probability distribution, allowing for finer resolution in regions where the signal is more likely to occur and coarser resolution elsewhere, thereby optimizing the signal-to-quantization-noise ratio. Examples of non-uniform quantization include A-law and mu-law companding, widely used in telecommunications.

The number of quantization levels, often determined by the number of bits used in the digital representation, directly affects the trade-off between accuracy and data size. More levels lead to higher accuracy but require more bits per sample. Selecting an appropriate quantization scheme is a crucial step in many digital systems, balancing desired fidelity with practical constraints on storage and bandwidth.