mirror of
https://github.com/hb9fxq/gr-digitalhf
synced 2024-11-05 05:55:53 +00:00
59 lines
1.2 KiB
C++
59 lines
1.2 KiB
C++
// -*- C++ -*-
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#include <cassert>
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#include "nlms.hpp"
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#include <volk/volk.h>
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namespace gr {
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namespace digitalhf {
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filter_update::sptr nlms::make(float mu, float delta) {
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return filter_update::sptr(new nlms(mu, delta));
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}
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nlms::nlms(float mu, float delta)
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: _mu(mu)
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, _delta(delta)
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, _gain()
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, _tmp()
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, _t1() {
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}
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nlms::~nlms() {
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}
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void nlms::resize(size_t n) {
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if (_gain.size() == n)
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return;
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_gain.resize(n);
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_tmp.resize(n);
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_t1.resize(n);
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std::fill_n(_gain.begin(), n, 0);
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}
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void nlms::reset() {
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std::fill_n(_gain.begin(), _gain.size(), 0);
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}
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gr_complex const* nlms::update(gr_complex const* beg,
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gr_complex const* end) {
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assert(end-beg > 0);
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size_t const n = end - beg;
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resize(n);
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volk_32fc_conjugate_32fc(&_tmp[0], beg, n);
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volk_32fc_magnitude_squared_32f(&_t1[0], beg, n);
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float norm = _delta;
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volk_32f_accumulator_s32f(&norm, &_t1[0], n);
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volk_32f_s32f_multiply_32f((float*)&_gain[0], (float const*)&_tmp[0], std::max(0.005f, _mu/norm), 2*n);
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return _gain.data();
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}
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void nlms::set_parameters(std::map<std::string, float>const & p) {
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_mu = p.at("mu");
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_delta = p.at("delta");
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}
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} // namespace digitalhf
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} // namespace gr
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