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using | obs_sized_vec = Eigen::Matrix< float_t, dimobs, 1 > |
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using | sampled_state_sized_vec = Eigen::Matrix< float_t, dim_s_state, 1 > |
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using | not_sampled_state_sized_vec = Eigen::Matrix< float_t, dim_ns_state, 1 > |
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using | dynamic_matrix = Eigen::Matrix< float_t, Eigen::Dynamic, Eigen::Dynamic > |
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using | func = std::function< const dynamic_matrix(const not_sampled_state_sized_vec &, const sampled_state_sized_vec &)> |
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using | func_vec = std::vector< func > |
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virtual void | filter (const obs_sized_vec &data, const func_vec &fs=func_vec())=0 |
| the filtering function that must be defined More...
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virtual | ~rbpf_base () |
| virtual destructor
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static constexpr unsigned int | dim_sampled_state = dim_s_state |
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static constexpr unsigned int | dim_not_sampled_state = dim_ns_state |
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static constexpr unsigned int | dim_obs = dimobs |
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◆ filter()
template<typename float_t , size_t dim_s_state, size_t dim_ns_state, size_t dimobs>
virtual void pf::bases::rbpf_base< float_t, dim_s_state, dim_ns_state, dimobs >::filter |
( |
const obs_sized_vec & |
data, |
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const func_vec & |
fs = func_vec() |
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) |
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pure virtual |
the filtering function that must be defined
- Parameters
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data | the most recent observation |
filter | functions whose expected value approx. is computed at each time step |
The documentation for this class was generated from the following file: