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In digital signal processing, downsampling, compression, and decimation are terms associated with the process of resampling in a multi-rate digital signal processing system. Both downsampling and decimation can be synonymous with compression , or they can describe an entire process of bandwidth reduction ( filtering ) and sample-rate reduction.
The frequency, f, in Hz is divided by the sample-rate. The periodicity and Nyquist frequency are then represented by constants, 1 and 1/2 respectively. The bottom pair depict a different normalized frequency scale, used by the Z-transform... the periodicity and Nyquist frequency are respectively represented by 2π and π.
Sample-rate conversion prevents changes in speed and pitch that would otherwise occur when transferring recorded material between such systems. More specific types of resampling include: upsampling or upscaling; downsampling, downscaling, or decimation; and interpolation.
The bandwidth, B, in this example is just small enough that the slower sampling does not cause overlap (aliasing). Sometimes, a sampled function is resampled at a lower rate by keeping only every M th sample and discarding the others, commonly called "decimation". Potential aliasing is prevented by lowpass-filtering the samples before decimation.
For example, if compact disc audio at 44,100 samples/second is upsampled by a factor of 5/4, the resulting sample-rate is 55,125. Fig 1: Depiction of one dot product, resulting in one output sample (in green), for the case L=4, n=9, j=3. Three conceptual "inserted zeros" are depicted between each pair of input samples.
A common example is the conversion of a sound wave to a sequence of "samples". A sample is a value of the signal at a point in time and/or space; this definition differs from the term's usage in statistics, which refers to a set of such values. [A] A sampler is a subsystem or operation that extracts samples from a continuous signal.
Lanczos windows for a = 1, 2, 3. Lanczos kernels for the cases a = 1, 2, and 3, with their frequency spectra. A sinc filter would have a cutoff at frequency 0.5. The effect of each input sample on the interpolated values is defined by the filter's reconstruction kernel L(x), called the Lanczos kernel.
Additionally, a semi-mechanistic downscaling approach can be applied as for example used for the CHELSA data of downscaled model output. In this example, the temperature algorithm is based on statistical downscaling and the precipitation algorithm incorporates orographic predictors with a subsequent bias correction. [7]