 |
SOLUTIONS
|
-
Functions
- Accumulate
- CellularAutomaton
- Clip
- Differences
- DiscreteWaveletTransform
- ExponentialMovingAverage
- FindFit
- Fit
- Fourier
- GaussianFilter
- Interpolation
- InverseFourier
- LaplacianFilter
- ListConvolve
- ListCorrelate
- ListDeconvolve
- MedianFilter
- MovingAverage
- MovingMedian
- Normalize
- Rescale
- Standardize
- WaveletThreshold
- WienerFilter
- Related Guides
- Tutorials
Data Transforms and Smoothing
Directly integrated into Mathematica's uniform architecture for handling lists of data is an array of highly optimized algorithms for transforming and smoothing datasets that can routinely involve millions of elements.
ReferenceReference
Rescale ▪ Clip ▪ Normalize ▪ Standardize ▪ Accumulate ▪ Differences
MovingAverage — find the simple moving average with any span
ExponentialMovingAverage — find the exponential moving average with damping
MovingMedian — find the moving median with any span
Interpolation — find an interpolation of any order in any number of dimensions
Fit — linear least-squares fit
FindFit — find a constrained nonlinear fit to data
ListConvolve, ListCorrelate — convolve or correlate data with any kernel
ListDeconvolve — restore convolved data
CellularAutomaton — apply a cellular automaton rule in any number of dimensions
Fourier, InverseFourier — discrete Fourier transform and inverse
Filters »
GaussianFilter ▪ LaplacianFilter ▪ WienerFilter ▪ MedianFilter ▪ ...
