Signal Filtering & Filter Design
Topic Overview In signal processing, the process of filtering a signal typically involves removing unwanted components such as noise and enhancing wanted features such as peaks or trends. Filters are systems that are designed to transform a signal in some desired way. Filters can be algorithms, mathematical models or electrical circuits. Filter design is the process of determining the filter components or coefficients to meet specific filtering requirements.
Filtering
ListConvolve — convolve a signal with a kernel
ListCorrelate ▪ ListDeconvolve ▪ MeanFilter ▪ GradientFilter
LowpassFilter — apply a smoothing filter to a signal
HighpassFilter ▪ BandpassFilter ▪ BandstopFilter ▪ HilbertFilter ▪ DifferentiatorFilter
GaussianFilter — perform a Gaussian or Gaussian derivatives filtering
DerivativeFilter ▪ LaplacianFilter ▪ WienerFilter ▪ MovingAverage
RecurrenceFilter — filter a signal using a linear recurrence equation
Digital Filter Design
LeastSquaresFilterKernel — generate an FIR filter by a least-squares method
FrequencySamplingFilterKernel ▪ EquirippleFilterKernel
ToDiscreteTimeModel — generate an IIR filter model from an analog prototype
Analog Filter Design
ButterworthFilterModel — create the transfer function of a Butterworth filter
BiquadraticFilterModel ▪ Chebyshev1FilterModel ▪ Chebyshev2FilterModel ▪ EllipticFilterModel ▪ BesselFilterModel
TransferFunctionModel — object representing a transfer-function model
BodePlot — plot the frequency response of a filter
TransferFunctionPoles ▪ TransferFunctionZeros ▪ TransferFunctionTransform ▪ StateSpaceModel ▪ ...
Window Functions »
KaiserWindow ▪ DirichletWindow ▪ HammingWindow ▪ BlackmanWindow ▪ ...
Discrete Transforms »
Fourier — Fourier transform of a signal (DFT)
ListZTransform ▪ ListFourierSequenceTransform ▪ DiscreteChirpZTransform ▪ ...
Wavelet Transforms »
DiscreteWaveletTransform — discrete wavelet transform (DWT)