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% ReBEL : Recursive Bayesian Estimation Library - Toolkit% Version 0.2%% ---CORE ROUTINES---%% ReBEL Inference System Routines% consistent - Check ReBEL data structures for consistency.% convgausns - Convert a Gaussian noise source from one cov_type to another.% fixinfds - Make a user defined InferenceDS data structure compliant.% geninfds - Generate a InferenceDS data structure from a user specified% general state space model (GSSM file).% gennoiseds - Generate a noise source data structure.% gensysnoiseds - Generate inference system noise sources (i.e. process and% observation noise sources).% gssm - TEMPLATE : General state space model template. Copy and adapt% for your own use.%% Inference Algorithms% cdkf - Central Difference Kalman Filter (SPKF family).% ekf - Extended Kalman Filter% gspf - Gaussian Sum Particle Filter% gmsppf - Gaussian Mixture Sigma-Point Particle Filter% kf - Kalman Filter (standard linear version)% pf - Generic Particle Filter (a.k.a Bootstrap or CONDENSATION)% sppf - Sigma-Point Particle Filter (Sigma-Point Filter family)% srcdkf - Square-Root Central Difference Kalman Filter (SPKF family)% srukf - Square-Root Unscented Kalman Filter (SPKF family)% ukf - Unscented Kalman Filter (SPKF family)%% Neural Neworks% mlpff - Feed forward a ReBEL MLP (multi-layer perceptron) neural% network.% mlpindexgen - Generate 'fast unpacking' index vectors for a ReBEL MLP neural% network.% mlpjacobian - Calculate neural network derivatives.% mlppack - Pack a ReBEL MLP neural network parameters (weights and biases)% into a single vector.% mlpunpack - Unpack a ReBEL MLP neural network parameter vector into seperate% weight and bias matrices.% mlpweightinit - Initialize the parameters of a ReBEL MLP neural network.%% Other Models% gauseval - Calculate the probability ( likelihood p(x|M) ) of a dataset% given a multivariate Gaussian density.% gaussamp - Sample from a multivariate Gaussian density.% gmmfit - Fit/train a Gaussian mixture model (GMM) to data using EM% gmminitialize - Initiliaze a GMM (used internally by gmmfit)% gmmsample - Sample efficiently from a GMM% gmmprobability - Calculate all probabilities relating a dataset to a GMM% (i.e. likelihoods, priors, evidence & posterior)%% Miscellaneous% addangle - Add two angles MOD 2pi radians.% addrelpath - Add and expand a relative path to the current MATLABPATH% checkdups - Check a vector for duplicate entries.% checkstructfields - Check if structure has a list of specified fields.% cvecrep - Column vector replicate.% datamat - Create a datamatrix from a vector of data% remrelpath - Remove a relative path from the current MATLABPATH% residualresample - Residual resampling needed by SIR algorithms% rvecrep - Row vector replicate% stringmatch - Match one string to a cell array of others.% subangle - Subtract two angles MOD 2pi radians.%
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