lmlib.statespace.cost

Definition of recursively computed squared error cost functions (such as Cost Segments and Composite Costs), all based on ALSSMs

Module Attributes

BACKWARD	Sets the recursion direction in a Segment to backward, use BACKWARD or BW
BW	Sets the recursion direction in a Segment to backward, use BACKWARD or BW
FORWARD	Sets the recursion direction in a Segment to forward, use FORWARD or FW
FW	Sets the recursion direction in a Segment to forward, use FORWARD or FW

Functions

create_rls(cost[, multi_channel_set, ...])	Returns a 'Recursive Least Squares Object' according to the provided parameters.
map_trajectories(trajectories, ks, K[, ...])	Maps trajectories at indices ks into a common target output vector of length K.
map_windows(windows, ks, K[, merge_ks, ...])	Maps the window amplitudes of one or multiple Segment to indices ks into a common target output vector of length K.

Classes

CompositeCost(alssms, segments, F, **kwargs)	Quadratic cost function defined by a conjunction one or multiple of Alssm and Segment
ConstrainMatrix(cost)	Constrain Matrix Generator
CostBase([label])	Abstract baseclass for CostSegment and CompositeCost
CostSegment(alssm, segment, **kwargs)	Quadratic cost function defined by an ALSSM and a Segment.
RLSAlssm(cost_model, **kwargs)	Filter and Data container for Recursive Least Sqaure Alssm Filters
RLSAlssmBase([betas])	Base Class for Recursive Least Square Alssm Classes
RLSAlssmSet(cost_model[, kappa_diag])	Filter and Data container for Recursive Least Sqaure Alssm Filters using Sets (multichannel parallel processing)
RLSAlssmSetSteadyState(cost_model[, ...])	Filter and Data container for Recursive Least Sqaure Alssm Filters using Sets in Steady State Mode
RLSAlssmSteadyState(cost_model[, ...])	Filter and Data container for Recursive Least Sqaure Alssm Filters in Steady State Mode
Segment(a, b, direction, g[, delta, label, ...])	Segment represents a window of finite or infinite interval borders used to select and weight signal samples in a cost function.

previous

lmlib.statespace.model.ModelBase

next

lmlib.statespace.cost.BACKWARD