Go to the source code of this file.
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| using | MayaFlux::Kinesis::Discrete::ConvolutionProcessor = std::function< void(const std::vector< std::complex< double > > &signal_fft, const std::vector< std::complex< double > > &kernel_fft, std::vector< std::complex< double > > &result_fft)> |
| | Frequency-domain processor callback for apply_convolution.
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| std::vector< double > | MayaFlux::Kinesis::Discrete::apply_convolution (std::span< const double > src, std::span< const double > kernel, const ConvolutionProcessor &processor, bool full_size=false) |
| | Core FFT convolution engine.
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| std::vector< double > | MayaFlux::Kinesis::Discrete::convolve (std::span< const double > src, std::span< const double > ir) |
| | Linear FFT convolution.
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| std::vector< double > | MayaFlux::Kinesis::Discrete::cross_correlate (std::span< const double > src, std::span< const double > tmpl, bool normalize=true) |
| | Cross-correlation via FFT.
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| std::vector< double > | MayaFlux::Kinesis::Discrete::matched_filter (std::span< const double > src, std::span< const double > reference) |
| | Matched filter (normalised cross-correlation)
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| std::vector< double > | MayaFlux::Kinesis::Discrete::deconvolve (std::span< const double > src, std::span< const double > ir, double regularization=1e-6) |
| | Frequency-domain deconvolution with Tikhonov regularisation.
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| std::vector< double > | MayaFlux::Kinesis::Discrete::auto_correlate (std::span< const double > src, bool normalize=true) |
| | Auto-correlation via FFT.
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