Matlab code that implements a state space filter for univariate Laplace-distributed data sequences, as detailed in the following paper:
- J. Neri, P. Depalle, R. Badeau, "Laplace State Space Filter with Exact Inference and Moment Matching," IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 5880-5884, Barcelona, Spain, 2020.
This Bayesian filter uses exact inference to infer the latent state sequence from temporal data. It successfully filters outliers and heavy-tailed noise, in addition to Laplace noise, Gaussian noise, and Cauchy noise. It is as fast as the Kalman filter.
The script demo.m runs a demonstration of the LSSF. Three different test data sequences are available to choose from: Laplace noise, outliers, and noise switch.