cross_correlate()

MAYAFLUX_API 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.

Parameters

src	Input signal
tmpl	Template signal
normalize	Normalise result to peak absolute value

Returns

Cross-correlation, same length as src

Definition at line 88 of file Convolution.cpp.

{
    std::vector<double> reversed(tmpl.rbegin(), tmpl.rend());
 
    auto out = apply_convolution(src, reversed,
        [](const auto& s, const auto& k, auto& r) {
            std::transform(std::execution::par_unseq, s.begin(), s.end(), k.begin(), r.begin(),
                [](const std::complex<double>& a, const std::complex<double>& b) {
                    return a * std::conj(b);
                });
        });
 
    if (normalize && !out.empty()) {
        const auto [mn, mx] = std::ranges::minmax_element(out);
        const double peak = std::max(std::abs(*mn), std::abs(*mx));
        if (peak > 0.0) {
            std::transform(std::execution::par_unseq, out.begin(), out.end(), out.begin(),
                [peak](double v) { return v / peak; });
        }
    }
 
    return out;
}

References a, apply_convolution(), b, normalize(), out, peak(), and src.

Referenced by matched_filter(), and MayaFlux::Yantra::ConvolutionTransformer< InputType, OutputType >::transform_implementation().

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