Parameterize abstract filters

[jamgochiana]

GaussianFilters.jl/src/ekf.jl

Lines 9 to 15 in 1aa2a64

	function predict(b0::GaussianBelief, u::Vector{a},
	filter::ExtendedKalmanFilter) where a<:Number
	# Motion update
	# Linear motion
	if filter.d isa LinearDynamicsModel

ExtendedKalmanFilter should be parameterized by DynamicsModel and ObservationModel types.

[zsunberg]

Parameterizing by the DynamicsModel and ObservationModel types will indeed yield significant performance improvement, but these parameters need not be present in function signatures, for example:

 function predict(b0::GaussianBelief, u::AbstractVector, filter::ExtendedKalmanFilter)

will have identical performance to

 function predict(b0::GaussianBelief, u::Vector{a}, filter::ExtendedKalmanFilter) where a<:Number

as you have now